Patent Description:
Huntington's disease is an inherited condition that leads to the progressive degeneration of nerve cells in the brain. A diagnosis of Huntington's disease may be based on neurological testing, genetic testing, and imaging, as well as family history and symptoms. The disease causes a wide variety of symptoms associated with motor function, cognitive function, behavioral function and functional capacity of the patient. Symptoms associated with motor function can include both involuntary movement problems and impairments in voluntary movements, such as involuntary jerking or writhing movements (chorea), muscle problems, such as rigidity or muscle contracture (dystonia), slow or abnormal eye movements, impaired gait, posture and balance, difficulty with the physical production of speech or swallowing. Impairments in voluntary movements can impact a person's ability to work, perform daily activities, communicate and remain independent. Although there is no known cure, treatments such as medications, therapies, and life style changes can help the patient cope with the symptoms of the disease. Additionally, the onset, severity and progression of the symptoms of Huntington's disease can vary between individuals. Thus, early detection of even small changes in the severity and progression of symptoms is important for guiding treatment and therapy options.

There are several standardized methods and tests for measuring the symptom severity and progression in patients diagnosed with Huntington's disease. Each of the tests involves a doctor measuring the subject's abilities to perform various mental and physical functions in different ways. These standardized tests can provide an assessment of the various symptoms associated with the patient's cognitive, behavioral, motor functions and capabilities and can help track changes in these symptoms over time. Assessing symptom severity and progression using standardized methods and tests can, therefore, help guide treatment and therapy options.

Currently, assessing the severity and progression of symptoms in a patient diagnosed with Huntington's disease involves in-clinic monitoring and testing of the patient every <NUM> to <NUM> months. While monitoring and testing a patient more frequently is ideal, increasing the frequency of in-clinic monitoring and testing can be costly and inconvenient to the patient. A prior art device for assessing Huntington's disease is known from
<CIT>.

The following presents a simplified summary of various aspects described herein. This summary is not an extensive overview, and is not intended to identify key or critical elements or to delineate the scope of the claims. The following summary merely presents some concepts in a simplified form as an introductory prelude to the more detailed description provided below. Aspects described herein describe specialized medical devices for assessing the severity and progression of symptoms for a patient diagnosed with Huntington's disease. Testing and monitoring may be done remotely and outside of a clinic environment, thereby providing lower cost, increased frequency, and simplified ease and convenience to the patient, resulting in improved detection of symptom progression, which in turn results in better treatment.

The invention relates to a diagnostic device for assessing one or more symptoms of Huntington's disease in a subject, the device comprising:.

characterized in that the computer-readable instructions, when executed by the at least one processor, further cause the device to:.

wherein the one or more diagnostic tasks are associated with a speed tapping test, wherein the subject is prompted to tap the display screen of the device as fast and as regularly as possible, using the index finger of both the left and right hands, wherein the speed tapping test measures the speed of finger movements.

A certain embodiment of the invention relates to the device as described herein, wherein the one or more symptoms of Huntington's disease in the subject include at least one of a symptom indicative of a cognitive function of the subject, a symptom indicative of a motor function of the subject, a symptom indicative of a behavioral function of the subject, or a symptom indicative of a functional capacity of the subject.

A certain embodiment of the invention relates to the device as described herein, wherein the one or more symptoms of Huntington's disease in the subject include at least one of a symptom indicative of a cognitive function of the subject, a symptom indicative of a motor function of the subject, a symptom indicative of a behavioral function of the subject, or a symptom indicative of a functional capacity of the subject, whereby the patient mobility is assessed at least partly based on GPS location data.

A certain embodiment of the invention relates to the device as described herein, wherein the one or more symptoms of Huntington's disease in the subject are indicative of at least one of visuo-motor integration, visual attention, motor speed, cognitive processing speed, chorea, dystonia, visuo-motor coordination, fine motor impairment, upper-body or lower-body bradykinesia.

A certain embodiment of the invention relates to the device as described herein, wherein the one or more sensors associated with the device further comprise at least one of a first sensor disposed within the device or a second sensor worn by the subject and configured to communicate with the device.

A certain embodiment of the invention relates to the device as described herein, wherein prompting the subject to perform the one or more diagnostic tasks further includes at least one of prompting the subject to answer one or more questions or prompting the subject to perform one or more actions.

A more complete understanding of aspects described herein and the advantages thereof may be acquired by referring to the following description in consideration of the accompanying drawings, in which like reference numbers indicate like features, and wherein:.

In the following description of various aspects, reference is made to the accompanying drawings, which form a part hereof, and in which is shown by way of illustration various embodiments in which aspects described herein may be practiced. It is to be understood that other aspects and/or embodiments may be utilized and structural and functional modifications may be made without departing from the scope of the described aspects and embodiments. Aspects described herein are capable of other embodiments and of being practiced or being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein are for the purpose of description and should not be regarded as limiting. Rather, the phrases and terms used herein are to be given their broadest interpretation and meaning. The use of "including" and "comprising" and variations thereof is meant to encompass the items listed thereafter and equivalents thereof as well as additional items and equivalents thereof. The use of the terms "mounted," "connected," "coupled," "positioned," "engaged" and similar terms, is meant to include both direct and indirect mounting, connecting, coupling, positioning and engaging.

Systems and devices described herein provide a diagnostic for assessing one or more symptoms of Huntington's disease in a patient. In some embodiments, the diagnostic may be provided to the patient as a software application installed on a mobile device.

In some embodiments, systems and devices described herein provide a diagnostic for assessing one or more symptoms of Huntington's disease in a patient based on passive monitoring of the patient. In some embodiments, the diagnostic obtains or receives sensor data from one or more sensors associated with the mobile device as the patient performs activities of daily life. In some embodiments, the sensors may be within the mobile device or wearable sensors. In some embodiments, the sensor features associated with the symptoms of Huntington's disease are extracted from the received or obtained sensor data. In some embodiments, the assessment of the symptom severity and progression of Huntington's disease in the patient is determined based on the extracted sensor features.

In some embodiments, systems, methods and devices according to the present disclosure provide a diagnostic for assessing one or more symptoms of Huntington's disease in a patient based on active testing of the patient. The claimed diagnostic device comprises a memory storing computer-readable instructions that, when executed by the at least one processor, cause the device to prompt the patient to perform one or more diagnostic tasks. The one or more diagnostic tasks are associated with a speed tapping test. In response to the patient performing the diagnostic task, the computer-readable instructions, when executed by the at least one processor, further cause the device to obtain or receive sensor data via one or more sensors. In some embodiments, the sensors may be within a mobile device or wearable sensors worn by the patient. Features associated with the symptoms of Huntington's disease are extracted from the received or obtained sensor data. In some embodiments, the assessment of the symptom severity and progression of Huntington's disease in the patient is determined based on the extracted features of the sensor data.

Assessments of symptom severity and progression of Huntington's disease using diagnostics according to the present disclosure correlate sufficiently with the assessments based on clinical results and may thus replace clinical patient monitoring and testing. Example diagnostics according to the present disclosure may be used in an out of clinic environment, and therefore have advantages in cost, ease of patient monitoring and convenience to the patient. This facilitates frequent patient monitoring and testing, resulting in a better understanding of the disease stage and provides insights about the disease that are useful to both the clinical and research community. An example diagnostic according to the present disclosure can provide earlier detection of even small changes in symptoms of Huntington's disease in a patient and can therefore be used for better disease management including individualized therapy.

<FIG> is a diagram of an example environment <NUM> in which a diagnostic device <NUM> for assessing one or more symptoms of Huntington's disease in a subject <NUM> is provided. In some embodiments, the device <NUM> may be a smartphone, a smartwatch or other mobile computing device. The device <NUM> includes a display screen <NUM>. In some embodiments, the display screen <NUM> may be a touchscreen. The device <NUM> includes at least one processor <NUM> and a memory <NUM> storing computer-instructions for a symptom monitoring application <NUM> that, when executed by the at least one processor <NUM>, cause the device <NUM> to assess the one or more symptoms of Huntington's disease in the subject <NUM> based on passive monitoring of the subject <NUM>. The device <NUM> receives a plurality of sensor data via one or more sensors associated with the device <NUM>. In some embodiments, the one or more sensors associated with the device is at least one of a sensor disposed within the device or a sensor worn by the subject and configured to communicate with the device. In <FIG>, the sensors associated with the device <NUM> include a first sensor 120a that is disposed within the device <NUM> and a second sensor 120b that is worn by the subject <NUM>. The device <NUM> receives a plurality of first sensor data via the first sensor 120a and a plurality of second sensor data via the second sensor 120b as the subject <NUM> performs activities of daily life.

The device <NUM> extracts, from the received first sensor data and second sensor data, features associated with one or more symptoms of Huntington's disease in the subject <NUM>. In some embodiments, the symptoms of Huntington's disease in the subject <NUM> may include a symptom indicative of a cognitive function of the subject <NUM>, a symptom indicative of a motor function of the subject <NUM>, a symptom indicative of a behavioral function of the subject <NUM>, or a symptom indicative of a functional capacity of the subject <NUM>. In some embodiments, the one or more symptoms of Huntington's disease in the subject <NUM> are indicative of at least one of visuo-motor integration, visual attention, motor speed, cognitive processing speed, chorea, dystonia, visuo-motor coordination, fine motor impairment, upper-body or lower-body bradykinesia.

In some embodiments, the first sensor 120a or second sensor 120b (or another sensor altogether) associated with the device <NUM> may include or interface with a satellite-based radio navigation system, such as may be used with the Global Positioning System (GPS), Galileo, GLONASS, and/or similar systems (collectively referred to herein as GPS), and the plurality of first sensor data received from the first sensor 120b may include location data associated with the device <NUM>. In some embodiments, the device <NUM> extracts location data, from the received first sensor data and second sensor data, associated with one or more symptoms of Huntington's disease in the subject <NUM>. In some embodiments, an assessment of motor function of the subject <NUM> may be based at least in part on the extracted location data (e.g., patient mobility may be assessed based in part on GPS location data). In some embodiments, the sensors <NUM> associated with the device <NUM> may include sensors associated with Bluetooth and WiFi functionality and the sensor data may include information associated with the Bluetooth and WiFi signals received by the sensors <NUM>. In some embodiments, the device <NUM> extracts data corresponding to the density of Bluetooth and WiFi signals received or transmitted by the device <NUM> or sensors, from the received first sensor data and second sensor data. In some embodiments, an assessment of behavioral function or an assessment of the functional capacity of the subject <NUM> may be based on the extracted Bluetooth and WiFi signal data (e.g., an assessment of patient sociability may be based in part on the density of Bluetooth and WiFi signals picked up).

The device <NUM> determines an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features of the received first and second sensor data. In some embodiments, the device <NUM> send the extracted features over a network <NUM> to a server <NUM>. The server <NUM> includes at least one processor <NUM> and a memory <NUM> storing computer-instructions for a symptom assessment application <NUM> that, when executed by the server processor <NUM>, cause the processor <NUM> to determine an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features received by the server <NUM> from the device <NUM>. In some embodiments, the symptom assessment application <NUM> may determine an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features of the sensor data received from the device <NUM> and a patient database <NUM> stored in the memory <NUM>. In some embodiments, the patient database <NUM> may include patient and/or clinical data. In some embodiments, the patient database <NUM> may include in-clinic and sensor-based measures of motor and cognitive function at baseline and longitudinal from early Huntington's disease patients. In some embodiments, the patient database <NUM> may include in-clinic and sensor-based measures of behavioral and other symptoms. In some embodiments, the patient database <NUM> may include data from patients at other stages of Huntington's disease. In some embodiments, the patient database <NUM> may be independent of the server <NUM>. In some embodiments, the server <NUM> sends the determined assessment of the one or more symptoms of Huntington's disease in the subject <NUM> to the device <NUM>. In some embodiments, the device <NUM> may output the assessment of the one or more symptoms of Huntington's disease. In some embodiments, the device <NUM> may communicate information to the subject <NUM> based on the assessment. In some embodiments, the assessment of the one or more symptoms of Huntington's disease may be communicated to a clinician that may determine individualized therapy for the subject <NUM> based on the assessment.

In some embodiments, the computer-instructions for the symptom monitoring application <NUM>, when executed by the at least one processor <NUM>, cause the device <NUM> to assess one or more symptoms of Huntington's disease in the subject <NUM> based on active testing of the subject <NUM>. The device <NUM> prompts the subject <NUM> to perform one or more diagnostic tasks. The one or more diagnostic tasks are associated with a speed tapping test. In some embodiments, prompting the subject to perform the one or more diagnostic tasks further includes prompting the subject to answer one or more questions or prompting the subject to perform one or more actions. In some embodiments, the diagnostic tasks are anchored in or modelled after well-established methods and standardized tests for evaluating and assessing Huntington's disease.

In response to the subject <NUM> performing the one or more diagnostic tasks, the diagnostic device <NUM> receives a plurality of sensor data via the one or more sensors associated with the device <NUM>. As mentioned above, the sensors associated with the device <NUM> may include a first sensor 120a that is disposed within the device <NUM> and a second sensor 120b that is worn by the subject <NUM>. The device <NUM> receives a plurality of first sensor data via the first sensor 120a and a plurality of second sensor data via the second sensor 120b. In some embodiments, the one or more diagnostic tasks may further be associated with at least one of a EQ-5D-<NUM> test, a WPAI-HD test, HD-SDI test, a draw a shape test using a left hand of the subject, a draw a shape test using a right hand of the subject, a chorea test, a balance test, a u-turn test, a SDMT test, and/or a word reading test.

The device <NUM> extracts, from the received plurality of first sensor data and the received plurality of second sensor data, features associated with one or more symptoms of Huntington's disease in the subject <NUM>. The symptoms of Huntington's disease in the subject <NUM> may include a symptom indicative of a cognitive function of the subject <NUM>, a symptom indicative of a motor function of the subject <NUM>, a symptom indicative of a behavioral function of the subject <NUM>, or a symptom indicative of a functional capacity of the subject <NUM>. In some embodiments, the one or more symptoms of Huntington's disease in the subject <NUM> are indicative of at least one of visuo-motor integration, visual attention, motor speed, cognitive processing speed, chorea, dystonia, visuo-motor coordination, fine motor impairment, upper-body or lower-body bradykinesia. As discussed above, location-based data from a GPS or similar system may be used to assess symptoms related to the motor function and/or mobility of the subject and other location based assessments. Similarly as discussed above, WiFi and Bluetooth signal density may be used, e.g., to help assess patent sociability.

The device <NUM> determines an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features of the received first and second sensor data. In some embodiments, the device <NUM> sends the extracted features over a network <NUM> to a server <NUM>. The server <NUM> may include at least one processor <NUM> and a memory <NUM> storing computer-instructions for a symptom assessment application <NUM> that, when executed by the server processor <NUM>, cause the processor <NUM> to determine an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features received by the server <NUM> from the device <NUM>. In some embodiments, the symptom assessment application <NUM> may determine an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features of the sensor data received from the device <NUM> and a patient database <NUM> stored in the memory <NUM>. In some embodiments, the patient database <NUM> may include patient and/or clinical data. In some embodiments, the patient database <NUM> may include in-clinic and sensor-based measures of motor and cognitive function at baseline and longitudinal from early Huntington's disease patients. In some embodiments, the patient database <NUM> may include in-clinic and sensor-based measures of behavioral and other symptoms. In some embodiments, the patient database <NUM> may include data from patients at other stages of Huntington's disease. In some embodiments, the patient database <NUM> may be independent of the server <NUM>. In some embodiments, the server <NUM> sends the determined assessment of the one or more symptoms of Huntington's disease in the subject <NUM> to the device <NUM>. In some embodiments, the device <NUM> may output the assessment of the one or more symptoms of Huntington's disease. In some embodiments, the device <NUM> may communicate information to the subject <NUM> based on the assessment. In some embodiments, the assessment of the one or more symptoms of Huntington's disease may be communicated to a clinician that may determine individualized therapy for the subject <NUM> based on the assessment.

<FIG> illustrates an example method <NUM> for assessing one or more symptoms of Huntington's disease in a subject (not part of the claimed subject-matter). based on passive monitoring of the subject using the example device <NUM> of <FIG>. While <FIG> is described with reference to <FIG>, it should be noted that the method steps of <FIG> may be performed by other systems. The method <NUM> for assessing one or more symptoms of Huntington's disease in a subject includes receiving a plurality of sensor data via one or more sensors associated with a device (step <NUM>). The method <NUM> includes extracting, from the received plurality of first sensor data, a plurality of features associated with the one or more symptoms of Huntington's disease in the subject (step <NUM>). The method <NUM> also includes determining a first assessment of the one or more symptoms of Huntington's disease based on the extracted features (step <NUM>).

<FIG> sets forth an example method <NUM> for assessing one or more symptoms of Huntington's disease using the example device <NUM> in <FIG>. In some embodiments, the device <NUM> may be a smartphone, a smartwatch or other mobile computing device. The device <NUM> includes at least one processor <NUM> and a memory <NUM> storing computer-instructions for a symptom monitoring application <NUM> that, when executed by the at least one processor <NUM>, cause the device <NUM> to assess the one or more symptoms of Huntington's disease in the subject <NUM> based on passive monitoring of the subject <NUM>.

In some embodiments, the symptom monitoring application <NUM> may provide a diagnostic application that includes a user interface (UI) that is displayed on the display screen <NUM> of the device <NUM>. In some embodiments, the display screen <NUM> may be a touchscreen and the user interacts with the diagnostic application via the displayed UI. <FIG> depict example screenshots, illustrating the UI of an example diagnostic application according to illustrative aspects described herein, and responsive UI changes to the user interface as a user interacts with the diagnostic application.

<FIG> depict example screenshots <NUM> and <NUM> illustrating pull-down menus of an example diagnostic application according to one or more illustrative aspects described herein. The screenshot <NUM> of <FIG> shows a first pull-down menu with the menu options "Overall Progress," "<NUM> Week Progress," "Backup Overview," and "Disk Overview," which a user can select, respectively, to instruct the diagnostic application to perform the requested menu action, and as further described below. <FIG> is a screenshot <NUM>, showing a second pull-down menu <NUM> with the menu options "Help," "About," "Settings," "Set Time Zone," "App ID," "Configure Watch," "Lock Watch," "Unlock Watch," "Initialize," "Begin Full Active Tests," and "Begin Cognitive Tests. " Similarly, when user selects one of the menu items, the diagnostic application performs the requested task or provides the requested information, and as further described below.

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, and <NUM> illustrating a selection of the menu options of the first pull-down menu shown in <FIG> according to according to one or more illustrative aspects described herein. As shown in the screenshot <NUM> of <FIG>, selecting the "Overall Progress" menu option displays information about the overall progress of the subject. As shown in the screenshot <NUM> of <FIG>, selecting the "<NUM> Week Progress" menu option displays information <NUM> about the biweekly progress of the subject. As shown in the screenshot <NUM> of <FIG>, selecting the "Backup Overview" menu option displays information about the uploading of files, for example, the number of files that are awaiting to be uploaded or the number of files that have already been uploaded. As shown in the screenshot <NUM> of <FIG>, selecting the "Disk Overview" menu option displays information about the memory usage of the device <NUM> associated with data of the diagnostic application.

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, and <NUM> illustrating a selection of various menu options of the second pull-down menu shown in <FIG> according to one or more illustrative aspects described herein. As shown in the screenshot <NUM> of <FIG>, selecting the "Help" menu option displays general information about the diagnostic application. As shown in the screenshot <NUM> of <FIG>, selecting the "About" menu option may display information including information about the application such as the Application ID, Version, Contact information, and various Copyright information. <FIG> is an example screenshot <NUM> showing additional information displayed by scrolling down past the information shown in the screenshot <NUM> of <FIG>. In some embodiments, the device <NUM> may be paired with a second device, such as a smartwatch. As shown in the screenshot <NUM> of <FIG>, selecting the "App ID" menu option displays information about the pairing between the device <NUM> and the second device. In some embodiments, the second device may be one or more wearable sensors, such as the second sensor 120b shown in <FIG>. In some embodiments, the second device may be any device that includes a motion sensor with an inertial measurement unit (IMU). In some embodiments, the second device may be a group of devices or sensors. The second device may comprise or be incorporated into a wearable such as a smart watch, electronic health monitor, and the like.

In some embodiments, the user may specify settings for passive monitoring of the user by the device <NUM> by selecting the "Settings" menu option of the second pull-down menu shown in <FIG>. <FIG> depict example screenshots <NUM>, <NUM> and <NUM> illustrating a selection of the "Settings" menu option of the second pull-down menu shown in <FIG> according to one or more illustrative aspects described herein. As shown in the screenshots <NUM> and <NUM> of <FIG>, selecting the "Settings" menu option displays various settings for "Passive Recording," such as "Pause location recording" and "Location pause duration". Selecting "Pause location recording" enables the user to pause location recording for a period of time. This pauses passive monitoring of the subject <NUM> by the device <NUM> for a period of time specified by "Location pause duration". The hour, minute and seconds of the period of time may be specified via a pop-up, as shown in the screenshot <NUM> of <FIG>. When the "Pause location recording" is disabled or not enabled, the device <NUM> receives a plurality of first sensor data via the first sensor 120a and a plurality of second sensor data via the second sensor 120b.

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and <NUM>, illustrating a selection of the "Initialize" menu option of the second pull-down menu shown in the screenshot <NUM> of <FIG> according to one or more illustrative aspects described herein. As shown in the screenshot <NUM> <FIG>, selecting the "Initialize" menu option of the second pull-down menu shown in the screenshot <NUM> of <FIG> displays a request for information for initializing the device <NUM>. In some embodiments, the requested information may be an initialization code. In some embodiments, the initialization of the device <NUM> is performed when the device <NUM> is initially given to the subject <NUM>. As shown in the screenshot <NUM> of <FIG>, a keypad may be displayed in order to enter the requested initialization information. Additionally, as shown in the screenshot <NUM> of <FIG>, information about the subject <NUM> may also be provided. As shown in the screenshot <NUM> of <FIG>, the requested subject information may include a "Screening ID," a "Subject ID," and a "Site ID. " As shown in the screenshot <NUM> of <FIG>, a pop-up keypad may be displayed. <FIG> depicts an example screenshot <NUM> requesting re-entry of the subject information if it is incorrect. As shown in the example screenshots <NUM> and <NUM> in <FIG>, if the subject information is requested, invalid formatting of the subject information is flagged for re-entry.

Referring back to <FIG>, the method <NUM> begins by proceeding to step <NUM> which includes receiving a plurality of sensor data via one or more sensors associated with the device <NUM>. During passive monitoring of the subject <NUM>, the device <NUM> receives a plurality of sensor data via one or more sensors associated with the device <NUM>. The sensors associated with the device <NUM> include a first sensor 120a that is disposed within the device <NUM> and a second sensor 120b that is worn by the subject <NUM>. The device <NUM> receives a plurality of first sensor data via the first sensor 120a and a plurality of second sensor data via the second sensor 120b.

Referring back to <FIG>, various aspects of passive monitoring may be specified via the user interface of the symptom monitoring application <NUM>. As shown in the example screenshots <NUM> and <NUM> of <FIG>, selecting the "Settings" menu option displays settings associated with "Passive Recording," such as "Pause location recording" and "Location pause duration. " Selecting "Pause location recording" <NUM> enables the user to pause location recording for a period of time. This pauses passive monitoring of the subject <NUM> by the device <NUM> for a period of time specified by "Location pause duration. " The hour, minute and seconds of the period of time may be specified via a pop-up, as shown in the screenshot <NUM> of <FIG>. When the "Pause location recording" is disabled or not enabled, the device <NUM> receives a plurality of first sensor data via the first sensor 120a and a plurality of second sensor data via the second sensor 120b.

The method <NUM> proceeds to step <NUM> which includes extracting, from the received first sensor data, a first plurality of features associated with the one or more symptoms of Huntington's disease in a subject. The device <NUM> extracts, from the received first sensor data and second sensor data, features associated with one or more symptoms of Huntington's disease in the subject <NUM>. The symptoms of Huntington's disease in the subject <NUM> may include a symptom indicative of a cognitive function of the subject <NUM>, a symptom indicative of a motor function of the subject <NUM>, a symptom indicative of a behavioral function of the subject <NUM>, or a symptom indicative of a functional capacity of the subject <NUM>. In some embodiments, the extracted features of the plurality of first and second sensor data may be indicative of symptoms of Huntington's disease such as visuo-motor integration, visual attention, motor speed, cognitive processing speed, chorea, dystonia, visuo-motor coordination, fine motor impairment, upper-body or lower-body bradykinesia.

The method <NUM> proceeds to step <NUM> which includes determining an assessment of the one or more symptoms of Huntington's disease based on the extracted features. The device <NUM> determines an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features of the received first and second sensor data. In some embodiments, the device <NUM> may send the extracted features over a network <NUM> to a server <NUM>. The server <NUM> includes at least one processor <NUM> and a memory <NUM> storing computer-instructions for a symptom assessment application <NUM> that, when executed by the processor <NUM>, determine an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features received by the server <NUM> from the device <NUM>. In some embodiments, the symptom assessment application <NUM> may determine an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features of sensor data received from the device <NUM> and a patient database <NUM> stored in the memory <NUM>. The patient database <NUM> may include various clinical and/or patient data. In some embodiments, the patient database <NUM> may include data, such as, in-clinic and sensor-based measures of motor and cognitive function at baseline and longitudinal from early Huntington's disease patients. In some embodiments, the patient database <NUM> may include in-clinic and sensor-based measures of behavioral and other symptoms. In some embodiments, the patient database <NUM> may include data of patients at other stages of Huntington's disease. In some embodiments, the patient database <NUM> may be independent of the server <NUM>. In some embodiments, the server <NUM> sends the determined assessment of the one or more symptoms of Huntington's disease in the subject <NUM> to the device <NUM>. In some embodiments, the device <NUM> may output the assessment of the one or more symptoms of Huntington's disease on the display <NUM> of the device <NUM>. In some embodiments, the assessment of the one or more symptoms of Huntington's disease may be communicated to a clinician that may determine individualized therapy for the subject <NUM> based on the assessment.

<FIG> illustrates an example method <NUM> for assessing one or more symptoms of Huntington's disease in a subject based on active testing of the subject using the example device <NUM> of <FIG>. While <FIG> is described with reference to <FIG>, it should be noted that the method steps of <FIG> may be performed by other systems. The method <NUM> includes prompting the subject to perform one or more diagnostic tasks (<NUM>). The method <NUM> includes receiving, in response to the subject performing the one or more tasks, a plurality of sensor data via the one or more sensors (step <NUM>). The method <NUM> includes extracting, from the received sensor data, a plurality of features associated with one or more symptoms of Huntington's disease (<NUM>). The method <NUM> includes determining an assessment of the one or more symptoms of Huntington's disease based on at least the extracted sensor data (step <NUM>).

<FIG> sets forth an example method <NUM> for assessing one or more symptoms of Huntington's disease based on active testing of the subject <NUM> using the example device <NUM> in <FIG>. In some embodiments, active testing of the subject <NUM> using the device <NUM> may be selected via the user interface of the symptom monitoring application <NUM>. <FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and <NUM> illustrating a selection of the "Begin Full Active Tests" menu option of the second pull-down menu <NUM> shown in <FIG> according to one or more illustrative aspects described herein. <FIG> is an example screenshot <NUM> of the second pull-down menu also shown in the screenshot <NUM> <FIG>. In some embodiments, upon selecting the "Begin Full Active Tests" menu option, the user interface may display a request for the Subject ID as shown in the example screenshots <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> of <FIG>. Upon entering the requested Subject ID information, the device <NUM> begins to perform active testing of the subject <NUM>.

The method <NUM> begins by proceeding to step <NUM> which includes prompting the subject to perform one or more diagnostic tasks. The device <NUM> prompts the subject <NUM> to perform one or more diagnostic tasks. In some embodiments, prompting the subject to perform the one or more diagnostic tasks includes prompting the subject to answer one or more questions or prompting the subject to perform one or more actions. In some embodiments, the diagnostic tasks are anchored in or modelled after well-established methods and standardized tests for evaluating and assessing Huntington's disease.

In some embodiments, the diagnostic tasks may include daily questions to assess the mood and physical health of the patient at the time of the active testing. The patient's response to the daily questions provide an assessment of the patient's daily mood fluctuations and may be used as a control when assessing symptoms associated with motor, cognitive and behavioral functions of the patient. <FIG> depict example screenshots <NUM> and <NUM> illustrating examples of daily questions according to some embodiments. <FIG> depicts an example screenshot <NUM> displaying an example daily question "How are you feeling physically right now?" The example screenshot <NUM> also shows displayed icons labelled "Excellent," "Good," "Fine," "Bad," and "Horrible. " The subject <NUM> chooses an answer by selecting the icon that best describes their health at that time. <FIG> depicts an example screenshot <NUM> displaying another example daily question "Overall, how is your mood right now?" The example screenshot <NUM> also shows icons labelled "Excellent," "Good," "Fine," "Bad," and "Horrible. " The subject <NUM> chooses an answer by selecting the icon that best describes their mood at that time.

In some embodiments, the diagnostic tasks may further implement a standardized test for measuring generic health status such as the EQ-5D-<NUM>. <FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and <NUM> illustrating an example EQ-5D-<NUM> test according to one or more illustrative aspects described herein. <FIG> is an example screenshot <NUM> displaying general instructions for an example EQ-5D-<NUM> test. <FIG> is an example screenshot <NUM> displaying various statements related to mobility, such as, "I have no problems walking," "I have slight problems walking," etc. The subject <NUM> is instructed to select the statement that best describes the mobility of the subject <NUM>. <FIG> is an example screenshot <NUM> displaying statements related to self-care, such as, "I have no problems washing or dressing myself," "I have slight problems washing or dressing myself," etc. The subject <NUM> is instructed to select the statement that best describes the self-care of the subject <NUM>. <FIG> is an example screenshot <NUM> displaying statements related to usual activities (e.g. work, study, housework, family or leisure activities) such as "I have no problems doing my usual activities," "I have slight problems doing my usual activities," etc. <FIG> is an example screenshot <NUM> related to the pain and discomfort experienced by the subject <NUM> and includes statements such as "I have no pain or discomfort," "I have slight pain or discomfort," etc. <FIG> is an example screenshot <NUM> displaying various statements related to anxiety and depression of the subject <NUM>. <FIG> depict example screenshots <NUM>, <NUM> and <NUM> illustrating some example questions related to the overall health of the subject <NUM>.

In some embodiments, the diagnostic tasks may further implement a Work Productivity and Activity Impairment Questionnaire specific to Huntington's disease (WPAI-HD). The diagnostic tasks associated with WPAI-HD measure the effect of Huntington's disease on the subject's ability to work and perform regular activities. <FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and <NUM> illustrating an example WPAI-HD according to one or more illustrative aspects described herein. In some embodiments, the diagnostic tasks may further prompt the subject to provide information about how many hours of work the subject missed because of problems associated with Huntington's disease including hours missed on sick days, the number of times the subject went in late to work, the number of times the subject left early from work. In some embodiments, the diagnostic tasks may prompt the subject <NUM> to provide information about how many hours the subject missed in the past seven days for reasons other than problems associated with Huntington's disease, such as, vacation, holidays, and time off to participate in a Huntington's disease study. In some embodiments, the diagnostic tasks may prompt the subject <NUM> to provide information about the number of hours the subject actually worked in the past seven days. In some embodiments, the diagnostic tasks may further prompt the subject <NUM> to provide information about how much the symptoms of Huntington's disease affected productivity while the subject was working. In some embodiments, the diagnostic tasks may further prompt the subject to provide information about how much the symptoms of Huntington's disease affected the subject's ability to perform regular daily activities unrelated to the subject's employment. Regular daily activities may include activities such as work around the house, shopping, childcare, exercising, studying.

In some embodiments, the diagnostic tasks further implement a Huntington's disease Speaking Difficult Item (HD-SDI). The diagnostic tasks associated with a HD-SDI test measure the effect of Huntington's disease on the subject's ability to speak. <FIG> depicts an example screenshot <NUM> illustrating an example HD-SDI test according to some embodiments. In some embodiments, the subject is prompted to provide information about how often the subject experienced difficult speaking recently.

The one or more diagnostic tasks are associated witha speeded tapping test. The diagnostic tasks prompt the subject <NUM> to tap the display screen <NUM> of the device <NUM> as fast and regularly as possible, using the index finger of both the left and right hands. The speeded tapping test measures the speed of finger movements. In some embodiments, the diagnostic tasks associated with the speed tapping test may assess symptoms of bradykinesia, chorea and/or dystonia. In some embodiments, the diagnostic tasks associated with the speed tapping test are modelled on tapping tests that have been shown to be sensitive to symptom changes in early Huntington's disease (Bechtel et al. <NUM>; Tabrizi et al. A similar finger tapping task is also included as part of the Unified Huntington's Disease Rating. Scale (UHDRS) assessment (Huntington's Study Group <NUM>).

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and <NUM> illustrating an example speeded tapping test according to one or more illustrative aspects described herein. As shown in the screenshot <NUM> of <FIG>, the subject is informed that the test is to be performed twice, once with each hand and the subject is prompted to select a hand to start with. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> selects the right hand. As shown in the screenshot <NUM> of <FIG>, the subject is instructed to tap a button displayed on the screen <NUM> of the device <NUM> with the right index finger as quickly and regularly as possible while resting the wrist and other fingers on the table. Next, as shown in the screenshot <NUM> of <FIG>, a countdown to the start of the test is displayed. The test begins and as shown in the screenshot <NUM> of <FIG>, a button is displayed on the screen <NUM> of the device <NUM>. The subject <NUM> taps the button on the screen <NUM> of the device <NUM> with the right index finger as quickly and regularly as possible. Next, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is prompted to continue the test with the left hand. As shown in the screenshot <NUM> of <FIG>, the subject is instructed to tap a button displayed on the screen <NUM> of the device <NUM> with the right index finger as quickly and regularly as possible while resting the wrist and other fingers on the table. As shown in the screenshot <NUM> of <FIG>, a countdown to the start of the test is displayed. The test starts and as shown in the screenshot <NUM> of <FIG>, a button is displayed on the screen <NUM> of the device <NUM>. The subject <NUM> taps the button on the screen <NUM> with the right index finger as quickly and regularly as possible. Then, as shown in the screenshot <NUM> of <FIG>, the test ends and the subject <NUM> is informed that the speeded tapping test is complete.

In some embodiments, the diagnostic application may include an instructional video for the speeded tapping test that the subject may view on the display screen <NUM> of the device <NUM>. <FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> from an instructional video for an example speeded tapping test according to one or more illustrative aspects described herein.

In some embodiments, the diagnostic tasks may further implement a draw a shape test that prompt the subject <NUM> to trace a series of increasingly complex shapes on the display screen <NUM> of the device <NUM>. In some embodiments, the shapes may include lines, a square, a circle, an eight, and a spiral. This test is designed to assess visuo-motor coordination and fine motor impairment in early Huntington's disease patients. The diagnostic tasks are modelled on circle tracing tasks that have been shown to be sensitive to symptom changes in the early stages of Huntington's disease (Say et al. <NUM>; Tabrizi et al.

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and <NUM> illustrating an example draw a shape test according to one or more illustrative aspects described herein. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test will be done twice, once with each hand. The subject <NUM> is prompted to select the hand to start with. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> selects the right hand to start with. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test measures fine motor movements. The subject <NUM> is instructed to trace a displayed shape and join the dots displayed along the outline of the shape, continuing in the direction of an arrow. The subject <NUM> is instructed to trace as quickly and as accurately as possible using the right index finger. Next, as shown in the screenshot <NUM> of <FIG>, a countdown to the start of the test is shown. Once the test begins, a shape is displayed on the screen. As shown in the screenshot <NUM> of <FIG>, a line is displayed. Several dots are also displayed along the line. Also displayed is an arrow indicating the direction in which the subject <NUM> should trace the shape along the dots. Using the right index finger, the subject <NUM> traces the line in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, a line, dots and arrow are displayed as in the screenshot <NUM> of <FIG>. However, the arrow is displayed in an opposite direction from the arrow displayed in the screenshot <NUM> of <FIG>. Using the right index finger, the subject <NUM> traces the line in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, an outline of a square with dots and an arrow are displayed. Using the right index finger, the subject <NUM> traces the square shape in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, an outline of a circle with dots and an arrow are displayed. Using the right index finger, the subject <NUM> traces the circle in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, an outline of a shape similar to the number eight with dots and an arrow are displayed. Using the right index finger, the subject <NUM> traces the shape in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, an outline of a spiral shape with dots and an arrow are displayed. Using the right index finger, the subject <NUM> traces the shape in the direction of the arrow.

The test is repeated with the left hand. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> is instructed to continue the test with the left hand. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test measures fine motor movements. The subject <NUM> is instructed to trace a displayed shape and join the dots displayed along the outline of the shape, continuing in the direction of an arrow. The subject <NUM> is instructed to trace as quickly and as accurately as possible using the left index finger. Next, as shown in the screenshot <NUM> of <FIG>, a countdown for beginning the test is shown. Once the test begins, a shape is displayed on the screen. As shown in the screenshot <NUM> of <FIG>, a line is displayed. Several dots are also displayed along the outline of the line. Also displayed is an arrow indicating the direction in which the subject <NUM> should trace the shape. Using the right index finger, the subject <NUM> traces the line in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, a line, dots and arrow are displayed as in the screenshot <NUM> of <FIG>. However, the arrow is displayed in an opposite direction from the arrow displayed in the screenshot <NUM> of <FIG>. Using the left index finger, the subject <NUM> traces the line in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, an outline of a square with dots and an arrow are displayed. Using the left index finger, the subject <NUM> traces the square shape in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, an outline of a circle with dots and an arrow are displayed. Using the left index finger, the subject <NUM> traces the circle in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, an outline of a shape similar to the number eight with dots and an arrow are displayed. Using the right index finger, the subject <NUM> traces the shape in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, an outline of a spiral shape with dots and an arrow are displayed. Using the right index finger, the subject <NUM> traces the shape in the direction of the arrow. Next, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test is complete.

In some embodiments, the diagnostic application may include an instructional video for the draw a shape test that the subject can view on the display screen <NUM> of the device <NUM>. 17A-17E depict example screenshots <NUM>, <NUM>, <NUM>, <NUM> and <NUM> from an example instructional video for a draw a shape test according to one or more illustrative aspects described herein.

In some embodiments, the diagnostic tasks further include a chorea test in which the subject <NUM> is prompted to hold the device <NUM> still in one hand with the corresponding arm outstretched, while wearing a wrist-worn wearable, such as the second sensor 120b shown in <FIG>. As a dual task, the subject <NUM> is also prompted to count backwards aloud. To ensure correct execution, the voice of the subject <NUM> is recorded. This test is designed to assess chorea and draws on other sensor-based approaches to measure chorea (Reilmann et al. <NUM>, <NUM>; Kegelmeyer et al. A chorea assessment is also part of the UHDRS (Huntington's Study Group <NUM>).

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> illustrating an example chorea test according to one or more illustrative aspects described herein. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test will be performed twice, once with each hand. The subject <NUM> is prompted to select the hand to start with. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> selects the right hand to start with. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test measures movements of the arms. The subject <NUM> is instructed to sit upright and hold the device <NUM> in the palm of the right hand with the display screen <NUM> of the device <NUM> facing up. The subject <NUM> is instructed to stretch the right arm out in front. The subject <NUM> is also instructed that when the buzzer of the phone vibrates, to close the eyes and count backwards out loud in sevens from <NUM>. The subject's voice is recorded. Next, as shown in the screenshot <NUM> of <FIG>, a countdown to the start of the test is shown. Once the test begins, a countdown to completion of the test is displayed, as shown in the screenshot <NUM> of <FIG>. The test is repeated using the left hand of the subject <NUM>. <FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> illustrating the test for the left hand. Then, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test is complete.

In some embodiments, the subject <NUM> the diagnostic application may include an instructional video for the chorea test that the subject can view on the display screen <NUM> of the device <NUM>. 19A-19E depict example screenshots <NUM>, <NUM>, <NUM>, <NUM> and <NUM> from an example instructional video for a chorea test according to one or more illustrative aspects described herein.

In some embodiments, the diagnostic tasks further implement a balance test. The subject <NUM> is instructed to stand still while wearing the device <NUM> and the wrist-worn wearable, such as sensor 120b shown in <FIG>. The balance test assesses the static balance function of the subject <NUM>. Sensor-based approaches for measuring static balance have been shown to be sensitive to differences in symptoms in early Huntington's disease (Dalton et al. The test is also part of established scales like the Berg Balance Scale (Berg et al. <NUM>), which are used in HD (Busse et al. <NUM>; Rao et al. The test is anchored to the UHDRS assessments for maximal dystonia, maximal chorea, and tandem walking (Huntington Study Group <NUM>).

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> illustrating an example balance test according to one or more illustrative aspects described herein. Before prompting the subject to perform the balance test, the subject <NUM> is instructed to answer several questions to assess whether it is safe for the subject <NUM> to perform the balance test. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> is asked whether the subject can stand and keep their balance safely. If the subject <NUM> selects the answer "No," the subject <NUM> is informed that the test will be skipped for safety reasons, as shown in the screenshot <NUM> of <FIG>. If the subject <NUM> selects the answer "Yes," then, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is asked whether the subject needs a walking aid to stand safely for <NUM> seconds. The subject selects "Yes" or "No." Next, as shown in the screenshot <NUM> of <FIG>, the subject is informed that the test measures balance. The subject is instructed to when the buzzer vibrates, to put both arms down, stand upright and maintain balance until the buzzer vibrates again. The subject is instructed to use a walking aid if needed to stand safely. Next, as shown in the screenshot <NUM> of <FIG>, the subject is instructed to place the phone in a running belt at waist height. The subject is also instructed to avoid pressing the phone's "Home" button. Next, as shown in the screenshot <NUM> of <FIG>, a countdown to the start of the test is displayed. The buzzer of the phone vibrates and the test is started. As shown in the screenshot <NUM> of <FIG>, a countdown to the end of the test is displayed. The subject performs the balance test as instructed by putting both arms down, standing upright and maintaining balance until the buzzer vibrates again, ending the test. Then, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test is complete.

In some embodiments, the diagnostic application may include an instructional video for the balance test that the subject <NUM> may view on the display screen <NUM> of the device <NUM>. <FIG> depict example screenshots <NUM>, <NUM>, <NUM> and <NUM> from an instructional video for an example balance test according to one or more illustrative aspects described herein.

In some embodiments, the diagnostic tasks may further implement a u-turn test. The subject <NUM> is instructed to walk and turn safely between two points that are at least four steps apart, while wearing the device <NUM> and the wrist-worn wearable, such as the second sensor 120b shown in <FIG>. In some embodiments, the subject <NUM> is instructed to make at least five turns. The test is designed to assess gait and lower-body bradykinesia, which are also assessed by the UHDRS. It is modelled on the Timed Up and Go Test, which has been clinically validated for the HD population (Busse et al. <NUM>; Rao et al. The test is anchored to the UHDRS gait, bradykinesia body, and tandem walking items (Huntington Study Group <NUM>).

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> illustrating an example u-turn test according to one or more illustrative aspects described herein. Before prompting the subject to perform the u-turn test, the subject <NUM> is instructed to answer several questions to assess whether it is safe for the subject <NUM> to actions associated with the u-turn test. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> is asked whether the subject can walk and turn safely. If the subject <NUM> selects the answer "No," the subject <NUM> is informed that the test will be skipped for safety reasons, as shown in the screenshot <NUM> of <FIG>. If the subject <NUM> selects the answer "Yes," then, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is asked whether the subject needs a walking aid to walk safely for approximately <NUM> meters or <NUM> feet. The subject is prompted to answer the question by selecting "Yes" or "No." Next, as shown in the screenshot <NUM> of <FIG>, the subject is informed that the test the subject's ability to walk and turn. The subject is instructed to walk between two points at least four steps apart, safely at a speed that is normal for the subject. The subject is instructed to start walking when the buzzer vibrates and complete at least five turns in <NUM> seconds until the buzzer vibrates again. The subject is also instructed to use a walking aid if needed to walk safely. Next, as shown in the screenshot <NUM> of <FIG>, the subject is instructed to carry the phone in front in a running belt at waist height. The subject is also instructed to avoid pressing the phone's "Home" button. Next, as shown in the screenshot <NUM> of <FIG>, a countdown to the start of the test is displayed. The buzzer of the phone vibrates and the test begins. As shown in the screenshot <NUM> of <FIG>, a countdown to the end of the test is displayed. The subject performs the actions of the u-turn test until the buzzer vibrates which ends the test. Then, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test is complete.

In some embodiments, the diagnostic application may include an instructional video for the u-turn test that the subject <NUM> may view on the display screen <NUM> of the device <NUM>. <FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> from an instructional video for an example u-turn test according to some embodiments.

In some embodiments, the diagnostic tasks may further implement a walk test. The subject <NUM> is instructed to walk as fast as is safely possible for <NUM> meters or <NUM> minutes every day. Preferably, the test is performed in a straight path with no obstacles (e.g., in a park). Sensor-based approaches for measuring gait have been shown to be sensitive to differences in symptoms in early HD (Dalton et al. The test is anchored to the UHDRS gait, bradykinesia body, and tandem walking items (Huntington Study Group <NUM>).

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> illustrating an example walk test according to one or more illustrative aspects described herein. Before prompting the subject to perform the walk test, the subject <NUM> is instructed to answer several questions to assess whether it is safe for the subject <NUM> to perform the actions associated with the walk test. As shown in the screenshot <NUM> of <FIG>, the subject <NUM> is asked whether the subject can walk safely of two minutes or about a distance of <NUM> meters or <NUM> feet. If the subject <NUM> answers "No," the subject <NUM> is informed that the test will be skipped for safety reasons, as shown in the screenshot <NUM> of <FIG>. If the subject <NUM> selects the answer "Yes," then, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is asked whether the subject needs a walking aid to walk safely for two minutes or about a distance of <NUM> meters or <NUM> feet. The subject is prompted to answer the question by selecting "Yes" or "No." Next, as shown in the screenshot <NUM> of <FIG>, the subject is informed that the test helps measure the subject's ability to walk. The subject is instructed to find a convenient place on even terrain where the subject can walk for two minutes or about <NUM> meters (<NUM> feet). The subject is instructed to safely walk as fast as possible. The subject is also informed that after two minutes, a beep and buzz by the device will indicate the end of the test. Next, as shown in the screenshot <NUM> of <FIG>, a countdown to the start of the test is displayed. The test begins and as shown in the screenshot <NUM> of <FIG>, a countdown to the end of the test is displayed. The subject performs the actions of the walk test. Then, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test is complete.

In some embodiments, the diagnostic tasks further include a Symbol Digit Modalities Test (SDMT) that may be modelled on the pen and paper SDMT (Smith, <NUM>). The subject <NUM> is prompted to match symbols with numbers according to a key as quickly and accurately as possible. The key, symbols, numbers are displayed on the display screen <NUM> of the device <NUM>. The SDMT test assesses visuo-motor integration, and measures visual attention and motor speed. The SDMT has been shown to be sensitive to symptom changes in early Huntington's disease patients (Tabrizi <NUM>) and is part of the Unified Huntington's Disease Rating Scale (UHDRS) assessment (Huntington's Study Group, <NUM>).

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, and <NUM> illustrating an example SDMT test according to one or more illustrative aspects described herein. As shown in the screenshot <NUM> of <FIG>, the subject is provided with instructions for the SDMT test. The instructions indicate that the test measures changes in how the subject's brain handles information. The subject <NUM> is prompted to match symbols with numbers according to a key as quickly and accurately as possible. The key, symbols, numbers are displayed on the display screen <NUM> of the device <NUM>. Next, as shown in the screenshot <NUM> of <FIG>, a countdown to the start of the test is displayed. The test begins and as shown in the screenshot <NUM> of <FIG>, a key, symbols, and numbers are displayed on the display screen <NUM> of the device <NUM>. The subject matches the symbols with the numbers according to the key as quickly and accurately as possible. Then, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test is complete.

In some embodiments, the diagnostic tasks further implement a word reading test. The subject is instructed to read aloud color words written in black font on the display screen <NUM> of the device <NUM>. The voice of the subject <NUM> is recorded. This test assesses cognitive processing speed, and is modelled on the "Word Reading" part of the Stroop Word Reading (SWR) Test (Ridley <NUM>). The "Word Reading" part of the SWR Test has been shown to be sensitive to symptom changes in patients with early Huntington's disease (Tabrizi <NUM>) and is part of the UHDRS assessment (Huntington's Study Group <NUM>).

<FIG> depict example screenshots <NUM>, <NUM>, <NUM>, and <NUM> illustrating an example word reading test according to one or more illustrative aspects described herein. As shown in the screenshot <NUM> of <FIG>, instructions for word reading are displayed on the display screen <NUM> of the device <NUM>. The instructions inform the subject that the test measures how the subject reads words. The subject is instructed to on the next screen, read out loud the words row by row and from left to right as fast as possible. The subject is instructed to start again from the top left unit the test ends if the subject finished reading all the words. Next, as shown in the screenshot <NUM> of <FIG>, a countdown to the start of the test is displayed. The test begins and as shown in the screenshot <NUM> of <FIG>, words arranged in rows are displayed on the screen <NUM> of the device <NUM>. The subject reads the words as instructed. Then, as shown in the screenshot <NUM> of <FIG>, the subject <NUM> is informed that the test is complete.

In some embodiments, the diagnostic application may include an instructional video for the word reading test that the subject may view on the display screen <NUM> of the device <NUM>. <FIG> depict example screenshots <NUM> and <NUM> from an instructional video for an example word reading test according to some embodiments.

In some embodiments, the diagnostic tasks are automatically scheduled and take about <NUM> minutes per day. In some embodiments, if the subject <NUM> does not complete the diagnostic tasks on the scheduled day, the scheduled tasks that occur less frequently than every second day (e.g., EQ-5D-SL, <NUM> Level Questionnaire, WPAI-HD, HD-SDI, Walk Test) are rolled over to the next time the diagnostic tasks are performed.

In some embodiments, the diagnostic application may display various messages or warnings unrelated to the active tests. <FIG> depict example screenshots illustrating the various messages and/or warnings displayed by the diagnostic application according to one or more illustrative aspects described herein.

The method <NUM> proceeds to step <NUM> which includes in response to the subject performing the one or more diagnostics tasks, receiving, a plurality of second sensor data via the one or more sensors. In response to the subject <NUM> performing the one or more diagnostic tasks, the diagnostic device <NUM> receives, a plurality of sensor data via the one or more sensors associated with the device <NUM>. As mentioned above, the sensors associated with the device <NUM> include a first sensor 120a that is disposed within the device <NUM> and a second sensor 120b that is worn by the subject <NUM>. The device <NUM> receives a plurality of first sensor data via the first sensor 120a and a plurality of second sensor data via the second sensor 120b.

The method <NUM> proceeds to step <NUM> including extracting, from the received sensor data, a second plurality of features associated with one or more symptoms of Huntington's disease. The device <NUM> extracts, from the received first sensor data and second sensor data, features associated with one or more symptoms of Huntington's disease in the subject <NUM>. The symptoms of Huntington's disease in the subject <NUM> may include a symptom indicative of a cognitive function of the subject <NUM>, a symptom indicative of a motor function of the subject <NUM>, a symptom indicative of a behavioral function of the subject <NUM>, or a symptom indicative of a functional capacity of the subject <NUM>. In some embodiments, the extracted features of the plurality of first and second sensor data may be indicative of symptoms of Huntington's disease such as visuo-motor integration, visual attention, motor speed, cognitive processing speed, chorea, dystonia, visuo-motor coordination, fine motor impairment, upper-body or lower-body bradykinesia. As discussed above, location-based data from a GPS or similar system may be used to assess symptoms related to the motor function and/or mobility of the subject and other location based assessments. Similarly, WiFi and Bluetooth signal density may be used to help assess patent sociability and the like.

The method <NUM> proceeds to step <NUM> which includes determining an assessment of the one or more symptoms of Huntington's disease based on at least the extracted sensor data. The device <NUM> determines an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features of the received first and second sensor data. In some embodiments, the device <NUM> may send the extracted features over a network <NUM> to a server <NUM>. The server <NUM> includes at least one processor <NUM> and a memory <NUM> storing computer-instructions for a symptom assessment application <NUM> that, when executed by the processor <NUM>, determine an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features received by the server <NUM> from the device <NUM>. In some embodiments, the symptom assessment application <NUM> may determine an assessment of the one or more symptoms of Huntington's disease in the subject <NUM> based on the extracted features of sensor data received from the device <NUM> and a patient database <NUM> stored in the memory <NUM>. The patient database <NUM> may include various clinical data. In some embodiments, the second device may be one or more wearable sensors. In some embodiments, the second device may be any device that includes a motion sensor with an inertial measurement unit (IMU). In some embodiments, the second device may be several devices or sensors. In some embodiments, the patient database <NUM> may be independent of the server <NUM>. In some embodiments, the server <NUM> sends the determined assessment of the one or more symptoms of Huntington's disease in the subject <NUM> to the device <NUM>. In some embodiments, such as in <FIG>, the device <NUM> may output an assessment of the one or more symptoms of Huntington's disease on the display <NUM> of the device <NUM>. In some embodiments, the assessment of the one or more symptoms of Huntington's disease may be communicated to a clinician that may determine individualized therapy for the subject <NUM> based on the assessment.

As discussed above, assessments of symptom severity and progression of Huntington's disease using diagnostics according to the present disclosure correlate sufficiently with the assessments based on clinical results and may thus replace clinical patient monitoring and testing. Diagnostics according to the present disclosure were studied in a group of Huntington's disease patients. The patients were provided with a smartphone application that included <NUM> active tests and continuous passive monitoring. The active tests included SDMT, Stroop word reading test, speeded tapping test, chorea test, balance test, U-turn test and two minutes long walk test. Data was collected over a period of two weeks <NUM> after in clinic screening visits for each patient. During the in-clinic screening visits, UHDRS scores, Symbol Digit Modalities Test (SDMT), Stroop Word Test and demographics related variables were collected for each patient.

<FIG> is a table showing various characteristics of the group of patients participating in a study. <FIG> is a graph showing the number of patients completing active tests per week for the first <NUM> weeks after the in-clinic screening visit. According to <FIG>, the patients completed, on average, <NUM> active tests per week. <FIG> is a graph showing the number of patients completing active tests per week for the first <NUM> weeks after the in-clinic screening visit. Additionally, there was no significant influence (all p><NUM>) on patient adherence to active testing on various factors such as age and gender, and disease severity (TMS, TFC and Independence Scale).

Sensor features were extracted from sensor data measured for each active test and aggregated over two-week periods starting with a baseline clinical visit. Intra-class correlation coefficients and Spearman correlations quantified test-retest reliability and validity compared to equivalent standard in-clinic tests or UHDRS items, respectively. <FIG> is a plot showing a correlation between results measured using a smartphone application's SDMT active test and results from standard in-clinic SDMT. <FIG> is a plot showing a correlation between results measured using the smartphone application's Stroop word reading active test and results from standard in-clinic Stroop word reading testing. <FIG> is a plot showing a correlation between the results measured using the smartphone application's speeded tapping active test and the results measured from standard in-clinic speeded tapping testing. <FIG> is a plot showing a correlation between results measured using the smartphone application's chorea test and results from standard in-clinic chorea assessment.

est-retest reliabilities of active tests ranged from <NUM>-<NUM>, median <NUM>. Diagnostics according to the present disclosure showed correlations with in-clinic testing ranging from r=<NUM> (p<<NUM>, Stroop word reading) to r=<NUM> (p<<NUM>, Speeded tapping). Active tests anchored to specific UHDRS items showed correlations ranging from r=-<NUM> (p=<NUM>, U-Turn) to r=<NUM> (p<<NUM>, Chorea non-dominant hand).

<FIG> illustrates one example of a network architecture and data processing device that may be used to implement one or more illustrative aspects described herein, such as the aspects described in <FIG>, <FIG> and <FIG>. Various network nodes <NUM>, <NUM>, <NUM>, and <NUM> may be interconnected via a wide area network (WAN) <NUM>, such as the Internet. Other networks may also or alternatively be used, including private intranets, corporate networks, LANs, wireless networks, personal networks (PAN), and the like. Network <NUM> is for illustration purposes and may be replaced with fewer or additional computer networks. A local area network (LAN) may have one or more of any known LAN topology and may use one or more of a variety of different protocols, such as Ethernet. Devices <NUM>, <NUM>, <NUM>, <NUM> and other devices (not shown) may be connected to one or more of the networks via twisted pair wires, coaxial cable, fiber optics, radio waves or other communication media.

The term "network" as used herein and depicted in the drawings refers not only to systems in which remote storage devices are coupled together via one or more communication paths, but also to stand-alone devices that may be coupled, from time to time, to such systems that have storage capability. Consequently, the term "network" includes not only a "physical network" but also a "content network," which is comprised of the data-attributable to a single entity-which resides across all physical networks.

The components may include data server <NUM>, web server <NUM>, and client computers <NUM>, <NUM>. Data server <NUM> provides overall access, control and administration of databases and control software for performing one or more illustrative aspects described herein. Data server <NUM> may be connected to web server <NUM> through which users interact with and obtain data as requested. Alternatively, data server <NUM> may act as a web server itself and be directly connected to the Internet. Data server <NUM> may be connected to web server <NUM> through the network <NUM> (e.g., the Internet), via direct or indirect connection, or via some other network. Users may interact with the data server <NUM> using remote computers <NUM>, <NUM>, e.g., using a web browser to connect to the data server <NUM> via one or more externally exposed web sites hosted by web server <NUM>. Client computers <NUM>, <NUM> may be used in concert with data server <NUM> to access data stored therein, or may be used for other purposes. For example, from client device <NUM> a user may access web server <NUM> using an Internet browser, as is known in the art, or by executing a software application that communicates with web server <NUM> and/or data server <NUM> over a computer network (such as the Internet). In some embodiments, the client computer <NUM> may be a smartphone, smartwatch or other mobile computing device, and may implement a diagnostic device, such as the device <NUM> shown in <FIG>. In some embodiments, the data server <NUM> may implement a server, such as the server <NUM> shown in <FIG>.

Servers and applications may be combined on the same physical machines, and retain separate virtual or logical addresses, or may reside on separate physical machines. <FIG> illustrates just one example of a network architecture that may be used, and those of skill in the art will appreciate that the specific network architecture and data processing devices used may vary, and are secondary to the functionality that they provide, as further described herein. For example, services provided by web server <NUM> and data server <NUM> may be combined on a single server.

Each component <NUM>, <NUM>, <NUM>, <NUM> may be any type of known computer, server, or data processing device. Data server <NUM>, e.g., may include a processor <NUM> controlling overall operation of the rate server <NUM>. Data server <NUM> may further include RAM <NUM>, ROM <NUM>, network interface <NUM>, input/output interfaces <NUM> (e.g., keyboard, mouse, display, printer, etc.), and memory <NUM>. I/O <NUM> may include a variety of interface units and drives for reading, writing, displaying, and/or printing data or files. Memory <NUM> may further store operating system software <NUM> for controlling overall operation of the data processing device <NUM>, control logic <NUM> for instructing data server <NUM> to perform aspects described herein, and other application software <NUM> providing secondary, support, and/or other functionality which may or may not be used in conjunction with other aspects described herein. The control logic may also be referred to herein as the data server software <NUM>. Functionality of the data server software may refer to operations or decisions made automatically based on rules coded into the control logic, made manually by a user providing input into the system, and/or a combination of automatic processing based on user input (e.g., queries, data updates, etc.).

Memory <NUM> may also store data used in performance of one or more aspects described herein, including a first database <NUM> and a second database <NUM>. In some embodiments, the first database may include the second database (e.g., as a separate table, report, etc.). That is, the information can be stored in a single database, or separated into different logical, virtual, or physical databases, depending on system design. Devices <NUM>, <NUM>, <NUM> may have similar or different architecture as described with respect to device <NUM>. Those of skill in the art will appreciate that the functionality of data processing device <NUM> (or device <NUM>, <NUM>, <NUM>) as described herein may be spread across multiple data processing devices, for example, to distribute processing load across multiple computers, to segregate transactions based on geographic location, user access level, quality of service (QoS), etc..

Claim 1:
A diagnostic device (<NUM>) for assessing one or more symptoms of Huntington's disease in a subject (<NUM>), the device comprising:
at least one processor (<NUM>) and a display screen (<NUM>);
one or more sensors (<NUM>) associated with the device; and
memory (<NUM>) storing computer-readable instructions that, when executed by the at least one processor, cause the device to:
receive a plurality of first sensor data via the one or more sensors associated with the device;
extract, from the received first sensor data, a first plurality of features associated with the one or more symptoms of Huntington's disease in the subject; and
determine a first assessment of the one or more symptoms of Huntington's disease based on the extracted first plurality of features,
characterized in that the computer-readable instructions, when executed by the at least one processor, further cause the device to:
prompt the subject to perform one or more diagnostic tasks;
in response to the subject performing the one or more diagnostic tasks, receive a plurality of second sensor data via the one or more sensors associated with the device;
extract, from the received second sensor data, a second plurality of features associated with the one or more symptoms of Huntington's disease; and
determine a second assessment of the one or more symptoms of Huntington's disease based on the extracted second plurality of features,
wherein the one or more diagnostic tasks are associated with a speed tapping test,
wherein the subject is prompted to tap the display screen of the device as fast and regularly as possible, using the index finger of both the left and right hands, wherein the speed tapping test measures the speed of finger movements.