Ambulatory patient monitoring apparatus, system and method

A patient monitoring device that combines physiological data collection with actigraphy data collection and associates the physiological data with synchronous actigraphy data. A method for processing actigraphy data by calculating absolute difference vectors of actigraphy signal vectors.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to automated non-invasive patient monitoring devices. Specifically, it relates to non-invasive patient monitoring devices which incorporate integrated actigraphy as a means for synchronizing physiological measurements with activity/rest cycles.

2. Description of the Related Art

Automated non-invasive patient monitoring devices such as the devices used in ambulatory blood pressure monitoring are well-known and commercially available. These devices enable clinicians to monitor a patient's physiological data during regular daily activity in the patient's everyday environment.

The human circadian or diurnal rhythm, including day-night patterns of vital signs, has a fundamental role in both in the proper diagnosis and treatment of patients. For example, almost all cardiovascular system functions, including heart rate, blood pressure, and blood flow exhibit circadian variability. Such rhythms in the physiological status of the cardiovascular system along with temporal patterns in the occurrence and intensity of environmental triggers of disease give rise to predictable-in-time differences in the susceptibility/resistance of persons to serious cardiovascular events such as heart attacks and strokes. As such, it is extremely valuable to have physiological data obtained on a patient correlated to their exact circadian rhythm including day-night patterns.

Existing physiological data monitors, whether home or clinic patient monitors as well as ambulatory patient monitors (see U.S. Pat. Nos. 4,830,018, 4,706,684, 6,251,080, 4,576,180, 4,967,756, 4,889,132), do not directly monitor and factor in the circadian or diurnal rhythm of a patient or include an integrated actigrapher. As such, they miss a critical component of the patient's conditions that would aid in better assessing the patient and developing a course of therapy optimized for that patient's conditions. Further, a comparison of two or more extended term (e.g., 24 hour) diagnostic data sets for a patient—such as that of a pre- and post-medication treatment—often fails to take into account subtle differences in the patient's circadian or diurnal rhythm. Any consideration for circadian rhythm variability is typically dependent on incomplete or imprecise statements or diaries from healthcare providers or patients which can drastically skew the results of any analysis or comparison.

Integrated actigraphy is critical to determine the patient's activity/rest patterns and to make possible automatic synchronization of pre-treatment and post-treatment recordings in order to evaluate the efficacy of treatment such as antihypertensive therapy. Integrated actigraphy is also critical in order to synchronize physiological recordings from different patients enrolled in clinical studies and clinical trials since each individual has different activity/rest patterns (for instance, patients wake up a different times).

Actigraphy has been recognized in prior art to identify circadian rhythms, sleep patterns, pharmacological treatment of hypertension, resynchronization of body clocks, etc. However, such prior art does not include the collection of physiological data over an extended basis in conjunction with actigraphy. As such, this prior art does not provide the ability to combine extended monitoring of physiological data along with actigraphy which are critical to correlating and analyzing patient conditions in response to circadian rhythm variations including asleep/awake patterns.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1shows a block diagram of a patient monitoring device100with actigraphy. The patient monitoring device100is configured to receive physiological sensor data from sensors (not shown) attached to a patient wearing the monitoring device100, associate the physiological sensor data with synchronous actigraphy data and store the associated physiological sensor and actigraphy data. The stored physiological sensor data and the associated actigraphy data can later be retrieved for analysis. Examples of sensors that may be used with the patient monitoring device100include, without limitation, blood pressure monitors, body temperature thermometers, electro-cardiograph electrodes, blood oxygen monitors and microphones.

The patient monitoring device100includes a sensor interface102, a processor108, a memory110, an actigrapher116and a computer interface114. The sensor interface102is configured to provide a signal path to the sensors. In some embodiments the sensor interface102is configured to provide a wireless signal path. In other embodiments, the sensor interface102is configured to provide a wireline signal path. The processor108is coupled with the sensor interface102and configured to receive physiological sensor data from the sensors. The processor108is coupled with the actigrapher116and configured to receive actigraphy data from the actigrapher116. The processor108is configured to associate physiological sensor data with actigraphy data and store the sensor and actigraphy data in the memory110. The computer interface114is configured to transfer stored physiological sensor data and associated actigraphy data from the patient monitoring device100to an external computer or storage device, where it can later be analyzed by medical professionals. In some embodiments, the computer interface114is configured to transfer instructions from the external computer to the patient monitoring device100.

The actigrapher116provides actigraphy data. Actigraphy data indicates a level of activity of the patient wearing the patient monitoring device100. In some embodiments the actigrapher116measures activity level with a 3-axis accelerometer, in which case, the actigraphy data includes measurements of acceleration. In other embodiments, the actigrapher116measures activity level with a gyroscope, and in yet other embodiments, with a tilt/inclination sensor.

In some embodiments, the patient monitoring device100includes transducers104and signal acquisition filters106. The transducers104are configured to receive physiological sensor data from the sensors through the sensor interface102and to convert the physiological sensor data from analog to digital. The signal acquisition filters106are configured to receive physiological sensor data from the transducers104, to filter out noise and extraneous signals, and to pass the filtered physiological sensor data to the processor108. In other embodiments, the functions provided by the transducers104and signal acquisition filters106are provided by devices external to the patient monitoring device100.

In some embodiments, the patient monitoring device100includes user controls112. The user controls112are configured to accept instructions from a user and transfer the instructions to the processor108. Other embodiments omit user controls112and instead receive instructions during manufacture of the patient monitoring device100or receive instructions through the computer interface114.

In some embodiments, the patient monitor includes a graphics controller118and a graphics user interface120. The graphics user interface120is configured to display information retrieved from the memory110for the user to view. The graphics controller118is configured to render the information retrieved from the memory110into a format usable by the graphics user interface120.

FIG. 2shows a flow chart of a method for processing actigraphy data. Some embodiments of the patient monitoring device100use this method. Other embodiments may use other methods.

Step200comprises measuring N number of actigraphy signal vectors during a sample window. The number N is equivalent to fstimes wl, where fsis the sample frequency and wlis the time width of the sample window. Each actigraphy signal vector represents actigraphy data taken during a particular sample. Each actigraphy signal vector has 3 components, one for each of 3 spatial axes (x, y, z). Each component represents a measured amount of acceleration along the respective axis during the particular sample. The actigraphy signal vectors are stored in an acceleration matrix Mi, as shown in Equation 1:
Mi=(x,y,z)  (1)

The acceleration matrix Micomprises N number of 3 dimensional actigraphy signal vectors. In some embodiments, the actigrapher116generates the actigraphy signal vectors.

Step202comprises calculating mean values for each of the axial components of the acceleration matrix Mi. The mean values are stored together as a mean acceleration vector mdc, as shown in Equation 2:
mdc=(x,y,z)  (2)

Step204comprises calculating a first order absolute difference vector (xd, yd, zd) for each of N actigraphy signal vectors in the acceleration matrix Mi. This is done by calculating for each of the N actigraphy signal vectors an absolute difference for each actigraphy signal vector component (x, y, z). Using k as an index of samples 1 to N, the absolute difference for each component of actigraphy signal vector k+1 is equal to the absolute value of the difference between the value of the vector component in sample k+1 minus the value of the vector component in sample k. The absolute difference vectors (xd, yd, zd) for the N actigraphy signal vectors are stored in an absolute difference matrix Md. Step204is performed in accordance with Equations 3-6:
xk+1d=|xk+1−xk|  (3)
yk+1d=|yk+1−yk|  (4)
zk+1d=|zk+1−zk|  (5)
Md=({xk+1d}k=1N,{yk+1d}k=1N,{zk+1d}k=1N)  (6)

Step206comprises calculating a sum of absolute differences for each vector component in the absolute difference matrix Md. The results are stored in an absolute difference vector m1. Step206is performed in accordance with Equations 7-8:

Step208comprises sequentially compiling absolute difference vectors components calculated during sequential sample windows and storing the results in a final matrix M. Step208is performed in accordance with Equation 9:
M={mk}k=1J={(x1,y1,z1)}k=1J(9)

where J is a duration in seconds of a recording session. Final matrix M can be associated with physiological data taking during the same time. Each biometric data point can be associated with a synchronous absolute difference vector m1.

FIG. 3shows one example of how the patient monitoring device100may be attached to the patient. The patient monitoring device100needs to be attached to the patient300while recording physiological data so as to simultaneously record actigraphy data. Patient300wears the patient monitoring device100attached to the patient's belt302. Alternatively, the patient monitoring device may be kept in a pocket in the patients clothing or attached to the patient via some other means.