Patent Description:
It is widely known that the blood pressure (BP) of a person typically drops or "dips" to a minimum value while the person is sleeping, a process driven by the diurnal biological rhythm. This reduction or dipping in BP is commonly defined as the ratio of the average sleeping (e.g. night-time or nocturnal) blood pressure to average waking (e.g. day-time) blood pressure, and it can occur in both systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean arterial (MAP) blood pressure values.

Such BP dipping is commonly categorized into the following four segments or categories:.

The absence of a decrease in sleeping blood pressure (BP) relative to waking BP is commonly referred to a "non-dipping" and it is associated with various health problems such as sleep-related problems (sleep disordered breathing (SDB) or insomnia, for example), obstructive sleep apnea (OSA), obesity, orthostatic hypotension, autonomic dysfunction, chronic kidney disease (CKD), diabetic neuropathy and old age. It has also been found to be an overall predictor of fatal and non-fatal mortality. Also, extreme dipping is associated with various health problems. BP dipping is therefore an important risk factor that should preferably be monitored and/or managed.

Known blood-pressure management or control concepts typically rely on the timed application (e.g. ingestion) of anti-hypertensive medication. However, such medication may have the drawbacks of being expensive, impractical and/or causing undesirable side-effects. Thus, there exists a need for BP monitoring and/or management concepts that are preferably non-invasive and/or don't require the administration of drugs/medication. Such non-invasive monitoring and/or drug-free concepts may be beneficial for enhanced diagnostics, therapy planning or general health in relation to many medical conditions, including CKD, sleep-related problems, OSA, obesity, and the like.

"<NPL>et al. and "<NPL>et al disclose effects of exercise on blood pressure.

<CIT> discloses a method of estimating stress caused by an exercise that includes receiving questionnaire data including body measurements from a user, measuring health measurement data, deducing an exercise target and an exercise prescription based on the received and measured data, and transmitting the exercise target and exercise prescription to the user. The questionnaire data is then received back from the user, including the body measurements from the user and measuring again the health measurements data; parameters are designed based on the received and re-received questionnaire data and the measured and remeasured health measurement data and the parameters are converted to predetermined values. A regression analysis model is designed for estimating the exercise stress using the parameters and performing regression analysis and the exercise stress estimated through the regression analysis is transmitted to the user.

The invention aims to at least partly fulfil one of the aforementioned needs. To this end, the invention provides devices, methods and computer program products as defined in the independent claims. The dependent claims provide advantageous embodiments. Thus, the invention provides an apparatus and a corresponding method for managing a blood-pressure variation (e.g. BP dipping) of a patient as defined in the independent claims.

Thus, there are proposed alternative, medication-free exercise-based concepts for managing or controlling BP dipping (including non-dipping or extreme dipping) through the combined timing and intensity of physical exercise. Such BP dipping typically occurs during sleep and so it is often referred to a nocturnal BP dipping or sleeping BP dipping.

Proposed embodiments are based on using the acute temporary anti-hypertensive benefits of exercise (known as post-exercise hypotension). Such benefits may also be combined with the finding that exercise-related signals in the brain also facilitate the synchronization of the internal circadian clock with the day-night cycle, improving the circadian rhythm. It is proposed to provide a personalised approach which prescribes exercise to a patient, wherein the timing and intensity of the exercise is set based on a measured BP dip of the patient and the patient's circadian rhythm (e.g. internal clock). In particular, embodiments may determine a prescribed (e.g. preferred or target) exercise intensity for an individual based on an obtained measure of a diurnal (e.g. sleeping) BP dip of the individual. Further, embodiments may determine a prescribed (e.g. preferred, advised or target) exercise timing for the individual based on an obtained measure of the individual's circadian rhythm. Based on the prescribed timing and intensity of exercise, a deficiency in the individual's BP dip may be resolved for example.

Proposed embodiments may therefore leverage information about an individual's BP variation(s) over the course of a predetermined time period (such as a day for example) in combination with information about the individual's circadian (e.g. <NUM>-hour) rhythm.

In this way, there may be provided a tool for managing a value of BP dipping that can be used by a medical professional, a general practitioner, or (medically) un-trained individual, for example. This may alleviate a need for close monitoring by medical professionals. It may also reduce a need for medical intervention or treatment. Embodiments may therefore relieve healthcare requirements/resources. Embodiments may also assist in the supervision or management of a patient at risk of health complications due to abnormal BP variations. Similarly, it may help as a preventative measure for persons who are at risk of developing health problems. Embodiments may also be used to verify the success of a prescribed activity or exercise and/or to monitor BP dipping progression or exacerbation.

The step of determining a target exercise timing for the patient comprises, as one option: determining a predicted timing of melatonin onset for the patient based on the measure of the circadian rhythm; and processing the predicted timing of melatonin onset in accordance with one or more algorithms to calculate the target exercise timing for the patient. In this way, embodiments may account for the patient's sleep pattern or expected time of sleeping so as to determine an optimal time for undertaking exercise to address a BP dip issue.

The step of determining a target exercise timing for the patient comprises, as another option, comparing the measure of circadian rhythm with a threshold value. Based on the result of the comparison, the target exercise timing may be determined to either be in a time window after waking or a time window before sleeping. For instance, embodiments may be adapted to determine whether a person is a 'morning person' or 'evening person' by comparing their internal diurnal rhythm to the world's day/night rhythm. For an evening person, the circadian rhythm may be compared with a first threshold value corresponding to melatonin onset time so as to derive a recommended exercise time window before sleep. For a morning person, the circadian rhythm may be compared with a second threshold value corresponding to a morning awakening so as to derive a recommended exercise time window after waking. Embodiments may thus be tailored to the specific circadian rhythm of a patient in order to provide optimal exercise prescriptions for managing BP variations of the patient.

The step of determining a target exercise intensity for the patient comprises: obtaining a waking blood pressure of the patient; calculating a target sleeping blood pressure for the patient based on the waking blood pressure and the measure of diurnal blood pressure dip of the patient; and calculating the target exercise intensity using an algorithm based on the target sleeping blood pressure. In this way, a BP differential between waking and sleeping may be obtained and then used to determine an optimal or preferred (i.e. target) sleeping BP for a patient. Using known or established relationships between exercise intensity and resultant BP variation, an exercise intensity for causing a BP variation to meet the optimal or preferred (i.e. target) sleeping BP may be determined.

Also, an embodiment may further comprise: obtaining an updated measure of a diurnal blood pressure dip of the patient, the updated measure being associated with a previously determined target exercise intensity; and modifying the algorithm based on the updated measure of a diurnal blood pressure dip of the patient and the previously determined target exercise intensity. In this way, the algorithm or function with which the target exercise intensity is calculated may be adapted (e.g. updated or calibrated) based on an actual observed result obtained using the target exercise intensity. For example, if one considers an example wherein, on day <NUM>, the target exercise intensity is determined to be <NUM>% to achieve a blood pressure decrease of <NUM> mmHg, a new or updated measurement may be obtained which indicates that, on day <NUM>, the achieved blood pressure decrease was actually <NUM> mmHg. The algorithm may then be adapted to propose a slightly lower exercise intensity in order to achieve a <NUM> mmHg decrease, since the updated measure indicates that the user has a stronger exercise response than the average person for example Such embodiments may therefore dynamically and automatically adapt to implementation specifics and/or characteristics of individuals.

Embodiments may further comprise sensing, with a sensor arrangement worn by or coupled to the patient, a value of at least one of: body temperature of the patient; activity of the patient; respiration rate of the patient; respiration rate variability of the patient; pulse rate of the patient; and pulse rate variability of the patient. A sensor output signal may then be generated based on the sensed value(s). Various physiological values or parameters of the patient may thus be obtained for the purpose of determining the circadian rhythm of the patient. One or more different approaches to determining the circadian rhythm may therefore be implemented, and such approaches may be combined for improved accuracy. Also, the ability to use various approaches to determine the circadian rhythm of the patient may enable embodiments to be adapted to various constraints, such as available resources, cost or complexity for example.

Further, embodiments may comprise receiving, at a processing unit, a sensor output signal from the sensor arrangement. The received sensor output signal may then be processed in accordance with one or more data processing algorithms to determine the measure of the circadian rhythm of the patient. Embodiments may further comprise sensing, with a BP sensing arrangement: a waking BP of the patient when awake; and a sleeping BP of the patient when asleep. A blood pressure output signal may then be generated based on the sensed value(s). Embodiments may therefore employ one or more sensors to obtain BP information about a patient and use this information for determining the diurnal BP dip of the patient. Alternative embodiments may, however, receive information regarding a measure of a diurnal BP dip of the patient from a separate or external method. Embodiments may therefore be modular in nature, or complete/contained methods that are adapted to sense/detect the information that may be needed for determining a BP dip and/or a circadian rhythm.

Proposed embodiments may further comprise receiving, at a processing unit, a blood pressure output signal from the blood pressure sensing arrangement. The received blood pressure output signal may then be processed in accordance with one or more data processing algorithms to determine the measure of the diurnal blood pressure dip of the patient.

Embodiments may therefore take account of a context of the patient, such as their current activity or physical properties for example.

Proposed embodiments may further comprise generating instructions for displaying a GUI on a display device using a processor device, wherein the graphical user interface is adapted to communicate information about the target exercise intensity and target exercise timing to a user. Generating instructions for display of a GUI can mean generating a control signal for use by a display device. Such instructions can be in the form of simple images such as bitmap JPEG or other format. However, such instructions can also be more complex allowing real time build-up of the GUI or parts of the GUI on a regular display device such as for example CRT, LCD, OLED, E-ink or the like.

According to another aspect, there may be provided a computer program product downloadable from a communications network and/or stored on a computer readable medium and/or microprocessor-executable medium wherein the computer program product comprises computer program code instructions, which when executed by at least one processor, implement a method according to a proposed embodiment. For example, by the apparatus according to the invention a user may be advised of a recommended timing and intensity to exercise at.

The exercise timing calculation unit may be adapted to: determine a predicted timing of melatonin onset for the patient based on the measure of the circadian rhythm; and process the predicted timing of melatonin onset in accordance with one or more algorithms to calculate the target exercise timing for the patient or may be adapted to: compare the measure of circadian rhythm with a threshold value; and based on the result of the comparison, determine the target exercise timing to either be in a time window after waking or a time window before sleeping.

The exercise intensity calculation unit is adapted to: obtain a waking blood pressure of the patient; calculate a target sleeping blood pressure for the patient based on the waking blood pressure and the measure of diurnal blood pressure dip of the patient; and calculate the target exercise intensity based on the target sleeping blood pressure.

Embodiments may further comprise a sensor arrangement adapted to be worn by or coupled to the patient, and to sense a value of at least one of: body temperature of the patient; activity of the patient; respiration rate of the patient; respiration rate variability of the patient; pulse rate of the patient; and pulse rate variability of the patient. The sensor arrangement may also generate a sensor output signal based on the sensed value(s).

In an embodiment, the apparatus may further comprise: a blood pressure sensing arrangement adapted to sense: a waking blood pressure of the patient when awake; and a sleeping blood pressure of the patient when asleep; and to generate a blood pressure output signal based on the sensed value(s).

Embodiments may further comprise a user input interface adapted to receive a user input signal representative of at least one of: patient information; and a limit value representative of an acceptable limit of a BP variation (e.g. BP dipping). Embodiments may therefore be thought of as providing an interface which enables a user to further specify information or data that may be relevant for the purpose of determining or monitoring a BP variation(s) and/or prescribed exercise timing and intensity. Such user-specified information may enable unique traits, circumstances and/or conditions specific to the user or the environment to be accounted for when determining or monitoring BP variation(s) and/or prescribed exercise timing and intensity.

Thus, there may be provided a tool which enables a user to further specify factors to be included in the determination or prescribed exercise timing and intensity. , e.g. by specifying a value or value range for a user attribute or activity. Embodiments may therefore provide input options, increasing the flexibility and power of BP dipping management.

In some embodiments, the apparatus may further comprise a communication interface adapted to communicate with one or more databases so as to obtain at least one of the information that may be used in determining or monitoring BP variation(s) and/or prescribed exercise timing and intensity.

There may be provided a portable computing device comprising apparatus for managing BP variation of a patient according to a proposed embodiment.

The system may further comprise a display device for displaying a graphical or non-graphical (e.g. auditory) user interface, wherein the graphical user interface is adapted to communicate information about prescribed exercise timing and intensity of a patient to a user.

Embodiments may comprise a client device comprising a data processor device. This may be a standalone device adapted to receive information from one or more remotely positioned information sources (via a communication link for example) and/or even adapted to access information stored in a database for example. In other words, a user (such as a medical professional, technician, researcher, patient etc.) may have an appropriately arranged client device (such as a laptop, tablet computer, mobile phone, PDA, etc.) which provides a system according to an embodiment and thus enables the user to provide data or information for the purpose of managing BP variation of a patient.

The system may comprise: a server device comprising the at least one processor, where the server device may be configured to transmit generated instructions for determining and/or displaying a BP variation and/or prescribed exercise timing and intensity to a client device or communication network. In such a configuration, display instructions are made available by a server. A user may therefore link with the server to work with the system.

The processor may be remotely located from the display device, and a control signal may thus be communicated to the display device via a communication link. Such a communication link can be e.g. the internet and/or a wireless communication link. Other suitable short-range or long-range communication links and/protocols may be employed. In this way, a user (such as a medical researcher, general practitioner, data analyst, engineer, patient etc.) may have an appropriately arranged device that can receive and process information according to an embodiment for managing a BP variation of a patient. Embodiments may therefore enable a user to remotely managing a BP variation of a patient using a portable computing device, such as a laptop, tablet computer, mobile phone, PDA, etc. Embodiments may also enable data retrieval after a monitored time period.

The system may further comprise: a server device comprising the at least one processor; and a client device comprising a display device. Dedicated data processing means may therefore be employed for the purpose managing a BP variation of a patient, thus reducing processing requirements or capabilities of other components or devices of the system.

Thus, it will be understood that processing capabilities may be distributed throughout the system in different ways according to predetermined constraints and/or availability of processing resources.

According to another aspect of the invention, there may be provided a portable computing device comprising apparatus for managing a blood-pressure variation of a patient according to proposed embodiments. For example, embodiments may be implemented in a wearable computing device, such as a smart watch or fitness tracker for example. In this way, the apparatus may be suitable positioned with respect to a patient so as to enable the gathering/obtaining of patient information that may be used for purpose of determining a diurnal blood pressure dip and/or a circadian rhythm of the patient. The portable computing device may, for example, be designed such the one or more sensors of the device can contact a carrier or wearer of the device.

Embodiments may provide concepts for managing BP variations of an individual/person. The proposed concepts may comprise determining both an intensity and timing of exercise to be undertaken by the individual so as to manage a diurnal BP variation of the individual (e.g. a BP dip when the individual is sleeping). Recommended exercise intensity may be calculated and prescribed for the individual based on measure of a diurnal BP dip which occurred when the individual slept. A recommended timing of the exercise may be calculated and prescribed for the individual based on measure of the circadian rhythm of the individual. Such prescribed exercise intensity and timing may then be communicated to the individual so as to instruct how to influence BP in a positive manner. For this purpose, proposed concepts may employ (or be employed on) at least one processor.

It will be understood that proposed embodiments may be applicable for any personal health programs or applications targeting blood pressure dipping. In particular, embodiments may be of particular benefit to individuals or patients who experience disrupted blood pressure dipping (e.g. non-dipping) such as shift worker and/or people suffering from sleep apnoea.

The independent claims define analogous advantages features for method and system/apparatus claims. The advantages explained for the method herein above and herein below may therefore also apply to the corresponding apparatus.

The invention will now be described in detail with reference to the following schematic drawings:.

Proposed embodiments relate to approaches and tools for managing BP variations or dipping of a patient.

In particular, it is proposed to leverage the understanding that physical exercise leads to a predictable, acute and temporary decrease in blood pressure of an individual. For example, physical exercise can acutely decrease the BP of an individual for a period of at least nine hours after the physical exercise. This decrease is known as post-exercise hypotension (PEH).

It has been identified that the effect of PEH on sleeping (e.g. nocturnal) blood pressure is dependent on a number of parameters including baseline BP, exercise intensity, exercise timing, and blood markers.

It has been found that the magnitude of PEH becomes stronger as baseline blood pressure increases. In subjects with a healthy blood pressure, PEH will be rather limited. In subjects with a high blood pressure, the effect of PEH can be strong enough to lower the blood pressure to healthy levels for a specific duration.

A linear dose-response relationship between the exercise intensity and the magnitude of PEH has been identified. For example, it has been found that an individual may experience a decrease of <NUM> mmHg in systolic BP per <NUM>% increase in oxygen uptake during exercise (relative to the maximum oxygen uptake).

In order for the BP lowering effects of PEH to affect the sleeping (e.g. nocturnal) BP, it is proposed that the exercise should be timed within a certain time window. By way of example, it has been identified that exercise in the evening will have a larger impact on the BP dip than exercise during the afternoon. However, this may need to be balanced against the consideration that exercise in the evening may not be undertaken very late in the night as it may have an adverse effect on sleep onset latency (and may also cause further complications in subpopulations, such as hot flashes in menopausal women for example). Accordingly, there may be a specific time window in which it is beneficial to exercise in the evening.

Some blood markers (glucose, cholesterol, etc.) have been found to correlate with the magnitude of PEH.

Taking account of the abovementioned parameters, it is proposed to manage or control BP dipping of an individual by determining both timing and intensity of physical exercise for the individual. In particular, it is proposed to provide a tailored approach which prescribes exercise to a patient, wherein the timing and intensity of the exercise is prescribed based on a measured BP dip of the patient and the patient's circadian rhythm (e.g. internal clock). More specifically, optimal or target exercise intensity is determined based on an obtained measure of a diurnal BP pressure dip of the individual. Further, an optimal or target timing of the exercise is determined based on an obtained measure of the individual's circadian rhythm. The determined values for exercise timing and intensity may then be adhered to by the individual so as to resolve an abnormal diurnal BP pressure dip for example.

Embodiments are therefore based on using the diurnal BP dip and circadian rhythm of an individual to recommend an intensity and time of exercise to be performed. This approach leverages the BP lowering effects of PEH combined with their time dependent nature so as to cater for a patient's circadian rhythm.

Embodiments may therefore be utilized to manage BP dipping in individuals and to better control healthcare or support therapy for patients with various health problems.

Also, the proposed invention may provide concepts for managing exercise parameters that can be employed by a general physician or (medically) un-trained person without the support of a trained medical professional. This may alleviate a need for medical professionals and/or medical intervention, thus potentially relieving healthcare requirements/resources.

Some embodiments may employ a sensor arrangement adapted to worn by or coupled to a patient. By way of example, the sensor arrangement may detect a value of at least one of: body temperature of the patient; activity of the patient; respiration rate of the patient; respiration rate variability of the patient; pulse rate of the patient; and pulse rate variability of the patient. Embodiments of the invention may therefore be utilized in conjunction with many different types of sensors and/or information databases that may provide information useful for determining a patient's BP and/or circadian rhythm and which more accurately accounts for the specific attributes of the patient, activity of the patient, and/or surrounding environment. A database may comprise, for instance, data relating to the individual's medical history or data relating to cardio-respiratory parameter values in different environmental conditions. For example, information or data employed by embodiments may comprise patient activity, vital signs, temperature, etc..

Embodiments may therefore provide a method, device and/or system that provides for user-specific management of BP dipping which takes account of contextual factors (including a physical attributes and activity of a patient, for example) in order to provide more accurate management of BP dipping. This may enable measurement and management of BP variations for a specific user, whilst enabling the user to partake in desired activities of daily life. Illustrative embodiments may therefore provide concepts which take account of rules and/or relationships relating to activity and physical attributes of the patient. Dynamic context-based BP dipping management may therefore be provided by proposed embodiments.

As a result, proposed embodiments may be of benefit in health programs or applications targeting blood pressure dipping, especially where users require tailored and/or accurate BP management. One such example may enable patients that are highly susceptible to BP dipping problems to gain a level of independence whilst still managing their potential exposure to BP dipping issues. This may, in turn, improve patient health, hospital efficiency, and available healthcare resources. Embodiments may therefore be of particular benefit for medical applications.

The following description provides a context for the description of elements and functionality of the invention and of how elements of the invention can be implemented.

In the description, the following terms and definitions are used.

BP dipping is the reduction or dipping in BP which is driven by the diurnal biological rhythm and typically occurs when a person sleeps. It can occur in both systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean arterial (MAP) blood pressure values. It is therefore often referred to as circadian, night-time, nocturnal or diurnal BP dipping and measured as the ratio of the average sleeping (e.g. night-time or nocturnal) BP to average waking (e.g. day-time) BP. A "non-dipper" is a person exhibiting an absence of a diurnal BP dip.

A graphical user interface (GUI) is a type of interface that allows users to interact with electronic devices through graphical icons and visual indicators such as secondary notation.

A display device is an electronic display device that can be controlled by a display control device. The display control device can be part of, or operate together with, a processor device.

Generating instructions for displaying a GUI can comprise (or be as simple as) constructing images (Bitmap, JPEG, Tiff or the like) of GUI views to be displayed on a display device using regular methods known in the art. Alternatively, such generation of instructions can comprise more dedicated instructions for real time build-up of a GUI view. The instructions can be in the form of a display control signal.

According to various embodiments, there are proposed several approaches to managing BP variations (such as BP dipping) of a patient.

Turning now to <FIG>, there is illustrated an apparatus for managing a blood-pressure variation of a patient according to an embodiment. In such an embodiment, the apparatus comprises a wearable BP sensing device <NUM> and a processing unit which is integrated in a portable computing device (e.g. a smartphone) <NUM>. Using a built-in communication interface, the portable computing device <NUM> can receive signals from the wearable BP sensing device <NUM> and other, supplementary sensors <NUM> and the process the received signals in accordance with one or more data processing algorithms to determine an exercise timing and intensity for a patient wearing the BP sensing device <NUM>. Further, using the conventional communication abilities of the portable computing device <NUM>, the device can communicate with one or more databases so as to obtain information that may be used in managing a BP variation of the patient. Such information may enable unique traits, circumstances and/or conditions specific to the user or the environment to be accounted for when how to manage a BP variation of the patient.

Also, a display <NUM> of the portable computing device <NUM> may be used to display a graphical user interface which communicates information about a determined (e.g. prescribed) exercise timing and intensity to a user of the device <NUM>.

In more detail, the embodiment of <FIG> comprises a wearable BP sensing device <NUM> that is integrated in a smartwatch <NUM> with communication abilities.

Here, the BP sensing device <NUM> is adapted to be worn by (or coupled to) the patient and a blood pressure sensing arrangement (not visible in <FIG>) adapted to sense: a (waking) blood pressure of the patient when awake; and a (sleeping) blood pressure of the patient when asleep. The BP sensing device <NUM> generates a blood pressure output signal based on the sensed value(s). In this way, the BP sensing device <NUM> is adapted to obtain information about a wearer's (e.g. the patient's) BP, wherein such information comprises (or can be used to determine) a measure of BP variations (e.g. a nocturnal BP pressure dip) of the patient.

The BP sensing device <NUM> of this embodiment also comprises a supplementary sensor arrangement (not visible in <FIG>) adapted to sense a value of at least one of: body temperature of the patient; activity of the patient; respiration rate of the patient; respiration rate variability of the patient; pulse rate of the patient; and pulse rate variability of the patient. The BP sensing device <NUM> is this adapted to sense values that comprise (or can be used to determine) a measure of the circadian rhythm of the patient.

Thus, in the example of <FIG>, the smartwatch <NUM> is adapted to obtain data or information (e.g. measurements, values, readings of patient parameters) relating to a BP dip of a patient and a circadian rhythm of the patient.

Based on the obtained data/information, the smartwatch <NUM> generates a sensor output signal for outputting to a signal/data processing unit, namely the smartphone <NUM> in the example of <FIG>.

Thus, in this embodiment, the signal/data processing unit is not integrated into the smartwatch <NUM>, but is instead provided as part of a portable computing device <NUM> that may be situated near the smartwatch <NUM> (e.g. within a few metres). Of course, in other embodiments, the signal processing unit may be integrated in the smartwatch <NUM>.

For communicating the sensor output signal to the portable computing device <NUM>, the smartwatch <NUM> comprises a communication interface (not shown) which is adapted to establish a wireless communication link with the portable computing device <NUM>. Any suitable short-range or long-range communication links and/protocols may be employed.

The portable computing device <NUM> namely a smartphone <NUM> (comprising data acquisition and processing components) is adapted to receive information from smartwatch <NUM> worn or carried by the patient via a wireless communication link.

The received sensor output signals from the smartwatch <NUM> thus comprises data that may be used (e.g. processed in accordance with an algorithm) so as to obtain a measure of sleeping BP dip of the patient and a measure of the circadian rhythm of the patient. These measures can then be used (e.g. processed in accordance with one or more algorithms) so as to determine a target exercise intensity and target exercise timing.

For example, the smartphone <NUM> of this example is adapted to implement a data processing algorithm which identifies a predicted timing of melatonin onset for the patient based on a measure of the patient's circadian rhythm. The algorithm then further processes the predicted timing of melatonin onset in accordance to calculate a target exercise timing for the patient. For instance, the processing unit <NUM> of the smartphone <NUM> can compare the measure of circadian rhythm with a predetermined threshold value and, based on the result of the comparison, can then determine the target exercise timing to either be in a time window after waking or a time window before sleeping.

Further, the smartphone <NUM> of this example is also adapted to implement a data processing algorithm which calculates a target sleeping BP for the patient based on an obtained measure of the patient's waking BP and an obtained measure of a diurnal BP dip of the patient. The algorithm then further processes the target sleeping blood pressure to calculate the target exercise intensity.

Furthermore, the smartphone <NUM> is also adapted to receive information from a supplementary sensor unit <NUM> which is adapted to sense a value of at least one of: movement; temperature; location, etc. The smartphone <NUM> is adapted to analyse the obtained measure of BP dip and/or circadian rhythm in combination with the received supplementary sensor <NUM> output signal(s) to determine at least one of: a refined BP dip and/or circadian rhythm value; an indication of accuracy or reliability; a sleep state of the patient; an activity of the patient; and an indication of event occurrence. In this way, a context of the patient (such as their current activity or physical properties for example) can be taken into account in the process of determining exercise timing and intensity for the patient.

The smartphone <NUM> is also adapted to send and/or receive information to/from a remotely located server <NUM> via the Internet <NUM>.

The information obtained by the smartphone <NUM> is processed to assess and identify factors which may influence the obtained measures of BP dip and/or circadian rhythm of the patient. By way of example, environmental information; patient information; and a limit value representative of an acceptable upper/lower limit of a BP dip may be used in the determination of exercise timing and intensity for a patient.

The information/data processing may be done by the smartphone <NUM>, by the 'Cloud', or by any combination thereof. The embodiment of <FIG> is therefore implemented as a distributed processing environment in which various types of information/data are processed so as to determine or monitor a cardio-respiratory function of the patient.

The smartphone <NUM> also comprises an output interface, namely a display <NUM> and speaker <NUM> arrangement, adapted to generate an output signal representative of the determined exercise timing and exercise intensity. For example, the user may be advised of timing to undertake a specific exercise program and guided via voice or visual prompts to undertake the exercise program in a manner which attempts to ensure that the correct exercise intensity is employed.

The smartphone <NUM> is also adapted to receive (e.g. via its touch sensitive screen <NUM>) a user input signal representative of at least one of: environmental information; patient information; and a limit value representative of an acceptable upper/lower limit of a cardio-respiratory value (such as BP, BP dipping heart rate, etc).

The smartphone <NUM> therefore provides an interface which enables a user to further specify information or data that may be relevant for the purpose of managing BP variations (such as diurnal BP dipping). Such user-specified information enables unique traits, circumstances and/or conditions specific to the user or the environment to be accounted for when managing BP variations. Put another way, the smartphone <NUM> enables a user to further specify factors to be included in the determination of exercise timing and intensity, e.g. by specifying a value or value range for a user attribute or activity. This provides many input options, increasing the flexibility and power of BP variation management.

Additionally, or alternatively, further environmental information and/or patient information may be provided by other sources or services. For example, local weather conditions and/or medical history data from a database of the server <NUM> can be used.

For example, in an exemplary implementation of the system of <FIG>, the server <NUM> comprises a data processor unit and is configured to transmit generated instructions for determining and/or displaying a determined exercise timing and intensity to a client device or communication network. In such a configuration, display instructions are made available by the server <NUM>. A user of the smartphone <NUM> can therefore link with the server <NUM> to work with the system. In this way, data processing means are remotely located from the portable computing device <NUM>, and a control signal can thus be communicated to the portable computing device <NUM> via a communication link (e.g. the Internet <NUM>).

Accordingly, a user is provided with an appropriately arranged device that can receive and process information relating to a cardio-respiratory function (such as BP) of a patient. Embodiments may therefore enable a user to monitor BP and BP dipping over time using a portable computing device, such as a laptop, tablet computer, mobile phone, PDA, etc. The portable computing device <NUM> therefore provides a tool that enables the user, for instance, to monitor their cardio-respiratory functions and undertake (or plan) appropriate exercise (to manage BP dipping for example) as they go about their normal daily activities. The user can obtain an understanding of their BP function, which then enables the user to continue or adapt their planned activities (depending on their tolerance to cardio-respiratory issues for example). Also, a medical professional, technician, researcher, etc. may have an appropriately arranged client device (such as a laptop, tablet computer, mobile phone, PDA, etc.) which is adapted to receive information relating to BP function of a monitored user (e.g. patient). In this way, a user can be provided with exercise guidance at a personal level which takes account of the unique attributes and/or activities of the user, and/or the surrounding environment. This alleviates a need for close monitoring by medical professionals or caregivers, for example. It may also reduce a need for medical intervention or treatment.

Dedicated data processing means can therefore be implemented at the server <NUM> for the purpose of determining a prescribed exercise timing and exercise intensity for a patient, thus relieving or reducing processing requirements at the portable computing device <NUM>.

Thus, it will be understood that processing capabilities may therefore be distributed throughout the system in different ways according to predetermined constraints and/or availability of processing resources of specific embodiments.

Turning now to <FIG>, there is depicted a flow diagram of a method <NUM> for managing a blood-pressure variation (e.g. BP dipping) of a patient according to an embodiment.

Step <NUM> comprises obtaining a measure of a diurnal blood pressure dip of the patient. Here, a blood pressure output signal is received (for example, at a processing unit) from a blood pressure sensing arrangement worn by the patient. By way of example, the blood pressure output signal of this embodiment comprises information relating to sensed values of: a waking BP of the patient when awake; and a sleeping BP of the patient when asleep. Such information may be used to determine the diurnal BP dip of the patient, for example by being processed in accordance with one or more data processing algorithms to determine the measure of the diurnal blood pressure dip of the patient. However, in alternative embodiments, the blood pressure output signal may comprise information regarding a measure of a diurnal BP dip of the patient (e.g. obtained from a separate or external method).

The obtained measure of diurnal blood pressure dip of the patient is passed to step <NUM> which comprises determining a target exercise intensity for the patient based on the obtained measure of diurnal blood pressure dip. In this example, determining a target exercise intensity for the patient comprises: obtaining a waking blood pressure of the patient (e.g. from the obtained blood pressure of a signal); and calculating a target sleeping blood pressure for the patient based on the waking blood pressure and the measure of diurnal blood pressure dip of the patient (as obtained in step <NUM>). The target exercise intensity is then calculated based on the target sleeping blood pressure. It will be appreciated that this process may be thought of as obtaining a BP differential which is then used to determine an optimal or preferred (i.e. target) sleeping BP for a patient. Using known or established relationships between exercise intensity and resultant BP variation, an exercise intensity for causing a BP variation to meet the optimal or preferred (i.e. target) sleeping BP can then be determined.

For instance, let one assume an example wherein the patient is a non-dipper, with a blood pressure dip of around <NUM>% (i.e. blood pressure during the night is equal to daytime), and the daytime systolic BP is <NUM> mmHg. If it is then desired for the nocturnal BP to be about <NUM>% lower, the preferred (i.e. target) sleeping BP may be calculated as <NUM>-(<NUM>*<NUM>)=<NUM> mmHg. This would indicate that, to have the desired nocturnal BP, the nocturnal BP should be <NUM> mmHg lower than the daytime value. If one then assumes that the systolic blood pressure drops with <NUM> mmHg per <NUM>% of VO2max (as has been reported in some published studies), a target may be calculated as <NUM>%*(<NUM>/<NUM>)=<NUM>% of VO2max. Calculation of the target exercise intensity can then be based on heart rate. For example, knowing the maximum heart rate, a target exercise intensity can be based on targeting <NUM>% of the maximum heart rate. For the example, if one assumes that the user's maximum heart rate is <NUM> BPM, a target heart rat can be calculated as <NUM>*<NUM>%=<NUM> BPM. Thus, the target exercise intensity can be recommended as aerobic exercise (of about half an hour) at the target heart rate of <NUM> BPM. Of course, it will be appreciated that there may be many other ways to calculate target exercise intensity.

Step <NUM> comprises obtaining a measure of the circadian rhythm of the patient. Here, a sensor output signal is received from a sensor arrangement coupled to the patient. The sensor arrangement provides the sensor output signal which includes information relating to a value of at least one of: body temperature of the patient; activity of the patient; respiration rate of the patient; respiration rate variability of the patient; pulse rate of the patient; and pulse rate variability of the patient. The received sensor output signal is processed in accordance with one or more data processing algorithms to determine the measure of the circadian rhythm of the patient. Nonetheless, since various physiological values or parameters of the patient may thus be obtained for the purpose of determining the circadian rhythm of the patient, one or more different approaches to obtaining a measure of the circadian rhythm may be implemented, and such approaches may be combined for improved accuracy.

The obtained measure of the circadian rhythm of the patient is passed to step <NUM> which comprises determining target exercise timing for the patient based on the obtained measure of the circadian rhythm. In this example, determining a target exercise timing comprises comparing the measure of circadian rhythm with a threshold value (in step <NUM>). Based on the result of the comparison, the target exercise timing may be determined to either be in a time window after waking or a time window before sleeping. More specifically, if, in step <NUM>, it is determined that the patient is a morning person (i.e. the circadian rhythm peaks is earlier than a predetermined average represented by the threshold), the method proceeds to step <NUM> wherein the target exercise timing is determined to be early in the morning, shortly after waking. If, on the other hand, it is determined (in step <NUM>) that the patient is an evening person (i.e. the circadian rhythm peaks later than the predetermined average represented by the threshold), the method proceeds to step <NUM> wherein the target exercise timing is determined to be in the evening prior to a predicted melatonin onset. In this regard, one can predict melatonin onset from the circadian rhythm, since it typically occurs <NUM> hours before sleep onset (which can be calculated based on the circadian rhythm).

Finally, in step <NUM>, an output signal representative of the target exercise intensity and target exercise timing is generated. By way of example, the output signal may be a control signal for a graphical user interface and thus comprise instructions for controlling the graphical user interface to display information about the target exercise intensity and target exercise timing.

The method <NUM> may thus provide a signal comprising information for managing or controlling BP dipping through the combined timing and intensity of physical exercise.

From the above description of the flow diagram in <FIG>, it will be understood that embodiments may provide a concept managing or controlling BP functions of a patient.

Although the embodiment of <FIG> has been described as comprising the steps of receiving output signals from separate sensing arrangements or methods, it should be understood that embodiments may comprise the additional step(s) of sensing a measure of BP dipping and/or circadian rhythm for a patient. By way of illustration, the flow diagram of <FIG> has been illustrated as also comprising the optional steps of <NUM> and <NUM> as indicated by dotted lines. For instance, the method <NUM> may include the step <NUM> of sensing a measure of BP dipping for the patient (e.g. using a BP sensing arrangement). Also, the method <NUM> may include the step <NUM> of sensing a measure of the circadian rhythm of the patient (e.g. using an arrangement of sensors for detecting values such as body temperature, pulse, blood pressure, etc.).

Turning now to <FIG>, there is depicted a flow diagram of an algorithm <NUM> according to an embodiment. The algorithm is adapted to prescribe the timing and intensity of exercise for restoring a deficiency in a blood pressure dip of a patient. By way of summary, the algorithm inputs comprise: (i) measured/detected internal circadian rhythm of the previous day(s); (ii) day-night rhythm of patient's time zone; and (iii) measured/detected BP dip of the previous day(s), and the algorithm output comprises a recommendation for the intensity and time of an exercise to be performed by the patient.

First, in step <NUM>, it is determined if the measured/detected BP dip of the previous day(s) is healthy. By way of example, this comprises determining if the BP dip is between <NUM>% and <NUM>%. If it is determined that the BP dip is within the predetermined healthy range (e.g. between <NUM>%-<NUM>%), the algorithm proceeds to step <NUM> wherein no specific recommendation is made (because the BP dip is considered healthy and no intervention in the patient's normal or current activities is deemed necessary).

If, however, it is determined (in step <NUM>) that the BP dip is not within the predetermined healthy range (e.g. between <NUM>%-<NUM>%), the algorithm proceeds to step <NUM> wherein it is determined if the measured internal circadian rhythm is within a predetermined acceptable range. By way of example, this comprises determining if the internal circadian rhythm is offset from the day-night rhythm of patient's time zone by less than <NUM> hour.

If it is determined (in step <NUM>) that the internal circadian rhythm is offset from the day-night rhythm of patient's time zone by more than <NUM> hour (i.e. not within the predetermined acceptable range), the algorithm proceeds to step <NUM> wherein the timing of the exercise is recommended to be at dawn or dusk (at moderate intensity) so as to exploit the circadian mechanisms for the restoration of the BP dip.

If, however, it is determined (in step <NUM>) that the internal circadian rhythm is offset from the day-night rhythm of patient's time zone by less than <NUM> hour (i.e. within the predetermined acceptable range), the algorithm proceeds to step <NUM> wherein it is determined if the BP dip is small. By way of example, this comprises determining (in step <NUM>) if the BP dip is less than <NUM>%.

If it is determined that the BP dip is small (e.g. less than <NUM>%), the algorithm proceeds to step <NUM> wherein a target exercise intensity is calculated. In this example, the step <NUM> of calculating a target exercise intensity comprises the following steps and calculations:.

From the above, it will be appreciated that proposed concepts may comprise the following components: BP dip monitoring (as an input); and internal circadian rhythm monitoring (as an input).

For BP dip monitoring, conventional or existing approaches may be implemented to monitor a patient's BP variations (e.g. nocturnal BP dip). By way of example, this can be an ambulatory blood pressure cuff that inflates automatically on a regular interval throughout the night or a smaller, less unobtrusive sensor integrated in a wearable computing device (such as a smartwatch or activity tracker for example).

For internal biological clock monitoring, various approaches may be implemented. An exemplary approach may, for example, employ core body temperature (CBT) monitoring, since CBT is regarded as an accurate reflection of the activity of the pacemaker a person's body clock. Measurements may be obtained using a temperature sensor (with IR-light, or another temperature measurement device) positioned in the ear, integrated in a wearable computing device, and/or using surrogate temperature measurements. Alternatively, or additionally, CBT may be obtained from a multitude of skin temperature sensors positioned on different parts of the body, preferably at distal locations. Alternatively, or additionally, measurements of physical activity can be used to determine circadian phase.

An exemplary approach for internal circadian rhythm monitoring may, for example, employ monitoring of pulse (e.g. inter-beat) intervals. Heart rate variability is a common measure of cardiovascular regulation by the autonomic nervous system. Using heart rate inter-beat intervals together with data from physical activity sensors, it can be possible to predict human circadian phase based on, as few as, only <NUM> hours of data. Such data can easily be recorded in ambulatory conditions. The heart rate intervals can be obtained in several ways, e.g. via ECG measurements using electrodes on the body or with photoplethysmography (PPG) sensors contained e.g. in spectacles, a wrist-worn device, or an in-ear device.

Yet another approach for internal circadian rhythm monitoring may comprise determining a current circadian phase using mathematical models of the human circadian pacemaker. Such models take ambient light levels and sleep-wake timing data as inputs and produce an estimate of the phase and amplitude of the circadian system. In propose embodiments, these models may additionally take the timing of the exercise into account.

It may be preferable for embodiments to recognize the phase of the current solar cycle. This can be easily done using an ambient light sensor built into any of the mentioned embodiments. Such a sensor will measure the variation of the ambient light intensity and is therefore able to determine episodes of dawn and dusk. In another embodiment, the phase of the current solar cycle can be determined based on the current geo-position of the user and the time-of-year. Both can be easily obtained using e.g. data from satellite positioning systems such as GPS or GLONASS, or data from other positioning systems using cellular techniques.

Proposed embodiments may be applicable for any personal health program targeting BP variations such as BP dipping. Disrupted BP variations (e.g. non-dipping) are a problem for shift work and/or sleep apnoea populations.

Is to be understood that proposed concepts may employ (or be employed on) at least one processor. Thus, there may be provided a computer program product downloadable from a communications network and/or stored on a computer readable medium and/or microprocessor-executable medium wherein the computer program product comprises computer program code instructions, which when executed by at least one processor, implement a method according to a proposed embodiment.

<FIG> illustrates an example of a computer <NUM> within which one or more parts of an embodiment may be employed. Various operations discussed above may utilize the capabilities of the computer <NUM>. For example, one or more parts of an apparatus for controlling blood pressure variation of a patient may be incorporated in any element, module, application, and/or component discussed herein.

The computer <NUM> includes, but is not limited to, PCs, workstations, laptops, PDAs, palm devices, servers, storages, and the like. Generally, in terms of hardware architecture, the computer <NUM> may include one or more processors <NUM>, memory <NUM>, and one or more I/O devices <NUM> (such as environmental sensors, infection source sensors, user susceptibility sensors, etc.) that are communicatively coupled via a local interface (not shown). The local interface can be, for example but not limited to, one or more buses or other wired or wireless connections, as is known in the art. The local interface may have additional elements, such as controllers, buffers (caches), drivers, repeaters, and receivers, to enable communications. Further, the local interface may include address, control, and/or data connections to enable appropriate communications among the aforementioned components.

The processor <NUM> is a hardware device for executing software that can be stored in the memory <NUM>. The processor <NUM> can be virtually any custom made or commercially available processor, a central processing unit (CPU), a digital signal processor (DSP), or an auxiliary processor among several processors associated with the computer <NUM>, and the processor <NUM> may be a semiconductor based microprocessor (in the form of a microchip) or a microprocessor.

The software in the memory <NUM> may include one or more separate programs, each of which comprises an ordered listing of executable instructions for implementing logical functions. The software in the memory <NUM> includes a suitable operating system (O/S) <NUM>, compiler <NUM>, source code <NUM>, and one or more applications <NUM> in accordance with exemplary embodiments. As illustrated, the application <NUM> comprises numerous functional components for implementing the features and operations of the exemplary embodiments. The application <NUM> of the computer <NUM> may represent various applications, computational units, logic, functional units, processes, operations, virtual entities, and/or modules in accordance with exemplary embodiments, but the application <NUM> is not meant to be a limitation.

Furthermore, the application <NUM> can be written as an object oriented programming language, which has classes of data and methods, or a procedure programming language, which has routines, subroutines, and/or functions, for example but not limited to, C, C++, C#, Pascal, BASIC, API calls, HTML, XHTML, XML, ASP scripts, FORTRAN, COBOL, Perl, Java, ADA,. NET, and the like.

If the computer <NUM> is a PC, workstation, intelligent device or the like, the software in the memory <NUM> may further include a basic input output system (BIOS) (omitted for simplicity). The BIOS is a set of essential software routines that initialize and test hardware at startup, start the O/S <NUM>, and support the transfer of data among the hardware devices. The BIOS is stored in some type of read-only-memory, such as ROM, PROM, EPROM, EEPROM or the like, so that the BIOS can be executed when the computer <NUM> is activated.

When the computer <NUM> is in operation, the processor <NUM> is configured to execute software stored within the memory <NUM>, to communicate data to and from the memory <NUM>, and to generally control operations of the computer <NUM> pursuant to the software. The application <NUM> and the O/S <NUM> are read, in whole or in part, by the processor <NUM>, perhaps buffered within the processor <NUM>, and then executed.

The computer readable medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium.

Thus, there is proposed a concept for providing user guidance regarding both the timing and intensity of exercise at a personal level which is based on a measure of a sleeping BP variation and circadian rhythm of a person. By employing information regarding the circadian rhythm of the person timing of exercise may be optimized so as to ensure appropriate timing of its temporary anti-hypertensive benefits which can manage/control a sleeping BP variation (e.g. BP dipping).

At this point, it is noted that the above described embodiments are merely example embodiments and that several extensions thereto and/or variations may be made.

For example, the employment of several types of monitoring/sensing devices can be envisaged, including clip-on devices, smart textiles, smartwatches, mouth inserts, etc..

Data from the system may be combined with personal data on health and well-being to generate a personal profile exercise and sleep prescriptions or programs. Data may also be transmitted for the benefit of other peer users or patients interested in cardio-respiratory functions, and such data could serve as an input to health monitoring software.

Other suitable extensions and variations to the above disclosed embodiments will be apparent to the skilled person.

For example, embodiments may be adapted to implement flexible thresholds that can be adapted according to user and/or with respect to time. In this way, it may be possible to have more or less strict versions of algorithms used to create exercise plans or prescriptions.

A preferred implementation may be to only inform a user when a BP variation (e.g. BP dip) issue or anomaly is detected. This may help to ensure a seamless solution without inhibiting social interaction.

The proposed concept has the advantage that a network of portable computing device with monitoring and/or communication functions can be easily transformed into a BP variation management system.

Aspects of the present invention may be embodied as a BP variation management method or system at least partially embodied by a portable computing device or distributed over separate entities including a portable computing device. Aspects of the present invention may take the form of a computer program product embodied in one or more computer-readable medium(s) having computer readable program code embodied thereon.

Such a system, apparatus or device may be accessible over any suitable network connection; for instance, the system, apparatus or device may be accessible over a network for retrieval of the computer readable program code over the network. Such a network may for instance be the Internet, a mobile communications network or the like. More specific examples (a non-exhaustive list) of the computer readable storage medium may include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fibre, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fibre cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for carrying out the methods of the present invention by execution on the processor <NUM> may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the processor <NUM> as a stand-alone software package, e.g. an app, or may be executed partly on the processor <NUM> and partly on a remote server. In the latter scenario, the remote server may be connected to the portable computing device <NUM> through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer, e.g. through the Internet using an Internet Service Provider.

Aspects of the present invention are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions to be executed in whole or in part on the data processor <NUM> of the system including portable computing device, such that the instructions create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable medium that can direct the system including the portable computing device to function in a particular manner.

The computer program instructions may, for example, be loaded onto the portable computing device <NUM> to cause a series of operational steps to be performed on the portable computing device <NUM> and/or the server <NUM>, to produce a computer-implemented process such that the instructions which execute on the portable computing device <NUM> and/or the server <NUM> provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. The computer program product may form part of a patient management system including a portable computing device.

Claim 1:
A method for managing a blood-pressure variation of a patient, the method comprising, by a processing unit:
obtaining (<NUM>) a measure of a nocturnal blood pressure dip of the patient;
determining (<NUM>) a target exercise intensity for the patient based on the obtained measure of the nocturnal blood pressure dip including
- obtaining a waking blood pressure of the patient,
- calculating a target sleeping blood pressure for the patient based on the waking blood pressure and the measure of nocturnal blood pressure dip of the patient, and
- calculating the target exercise intensity based on the target sleeping blood pressure;
obtaining (<NUM>) a measure of the circadian rhythm of the patient;
determining (<NUM>) a target exercise timing for the patient based on the obtained measure of the circadian rhythm including
- determining a predicted timing of melatonin onset for the patient based on the measure of the circadian rhythm and processing the predicted timing of melatonin onset in accordance with one or more algorithms to calculate the target exercise timing for the patient; or
- comparing the measure of circadian rhythm with a threshold value and, based on the result of the comparison and determining the target exercise timing to either be in a time window after waking or a time window before sleeping; and
generating (<NUM>) an output signal representative of the target exercise intensity and target exercise timing.