Surgery – Diagnostic testing
Reexamination Certificate
2000-02-28
2002-08-27
Shaver, Kevin (Department: 3736)
Surgery
Diagnostic testing
C600S546000, C128S920000, C128S925000
Reexamination Certificate
active
06440067
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates to a computer-based method and system for remotely monitoring physical activity in a continuous and unobtrusive fashion while an individual performs normal and usual activities of daily living.
With continuing emphasis placed on the financial management of health care, it is inevitable that a growing number of patients in need of physical rehabilitation will be channeled to receive a significant part of their rehabilitation in the home. This trend is both financially as well as practically driven to ensure that the limited available resources are used effectively. It also focuses care towards independent functioning at home or under assisted-living conditions rather than extended institutional care or overuse of clinical services.
Health providers need condensed and specific information to describe the physical and functional performance of their patients in the home or other remote location, without relying on self-reports or having the patient leave the home. For example, objective parametric measures are needed to describe how physically active the patient has been, and the type and degree of activities of daily living (such as walking, stairclimbing, feeding, grooming, dressing, exercise, etc.) he/she has performed during a specified period of time. Having this information readily available to the health provider can augment clinical service by making the home a more effective place for rehabilitation, especially for the elderly patient, or person with neurological disorders.
At last two groups of patients can benefit from home-based monitoring of Functional Activities. The first consists of those patients who are discharged to the home setting after inpatient rehabilitation. The current model of care relies on regular updates of a patient's functional status. These updates are currently provided on a relatively infrequent basis and are often based on self-reports or limited observation of the patient's activity. Self-reports can be vague or inaccurate due to poor memory or misconceptions, or biased by the variable amount of assistance provided. Observer rated surveys are often time consuming and do not reflect changes in performance that may occur during the patient's day. A second group of patients that can benefit from home-based monitoring of Functional Activities are those “at risk” of significant functional decline. These patients are typically followed as outpatients in hospital based clinics, or are followed through home care services. Both approaches to care have significant drawbacks. The hospital based approach typically consists of relatively infrequent visits that are often inconvenient for the patient and are expensive for the health care system. This approach also has the disadvantage of taking the patient out of their usual environment so that information about functional abilities is based on self-report or on a limited functional examination in the hospital setting, which typically does not adequately approximate the patient's own home environment. The home-based approach is also expensive and typically involves limited observation of the patient's functional performance for a period of several hours per day, often limited to less than 5 days per week. Decisions about increasing or decreasing the amount of services are thus based on a limited data set that may not reflect the patient's true abilities and needs.
By monitoring a patient in “real time”, adjustments to the patient's support services can be made quickly. This approach has the obvious advantage of providing the appropriate amount of assistance required. It also has the potential to significantly reduce costs of care, by providing assistance as soon as it is required, rather than waiting for the deleterious effects of a person's inability to care for themselves to manifest as poor nutrition or hygiene. When these conditions occur, the patient often re-enters the inpatient health care system. When the ultimate outcome is institutionalization, the quality of life decreases and the cost of care goes up substantially. Measuring a patient's true performance of functional motor tasks automatically in the home would provide a means for assessing the extent to which a patient is able to provide their own self-care. For example, a patient who is physically able to perform their activities of daily living with supervision or cueing might not actually perform them if left on their own. In the current system of care, such a patient would likely receive fewer services than would actually be required. Only when the results of a lack of appropriate self-care become apparent would the amount of services be re-evaluated.
The object of the present invention, therefore, is to provide a system for monitoring remotely the amount and kinds of physical activity that a patient or other user conducts throughout a given time period.
SUMMARY OF THE INVENTION
The invention is a method for remotely monitoring and identifying Functional Activities performed by a test subject, the method includes the steps of (a) extracting a given type of signals from each of a predetermined set of muscles of a control subject during the performance thereby of a given Functional Activity; (b) processing the signals to provide therefor given parameters affected by the given Functional Activity; (c) storing the data obtained in step (b); and (d) repeating steps (a)-(c) for a plurality of other control subjects. The stored data then is utilized to establish a normative data base indicative of the given Functional Activity and further steps include: (f) extracting the given type of signals from each of at least some of the predetermined set of muscles of a test subject during a given monitoring period; and (g) comparing the data base to the signals of step (f) to identify during the monitoring period portions thereof during which the test subject was performing the given Functional Activity. The method can be used unobtrusively in a home environment to monitor the degree and type of motor activity of various test subjects.
According to one feature of the invention, step (e) includes passing the data through a classification algorithm to identify specific signal patterns which correspond to the given Functional Activity. Identification of useful signal patterns is facilitated with the use of algorithms.
According to another feature, the muscle includes a predetermined number of muscles, step (e) includes identifying for the data base those signals extracted from a portion of the muscles having patterns most dependent on the given Functional Activity, and step (f) comprises extracting the signals only from that portion of the muscles. This feature improves response time of the method.
According to other features of the invention, the signals are biosignals, preferably Electromyographic (EMG) signals and the given parameters include at least some taken from a group including root-mean square value, envelope, mean rectified value and frequency characteristics. These features provide data highly effective in Functional Activity identification.
According to still other features of the invention, step (a) includes attaching a sensor over each of the muscles which include either the Deltoid and the Erector Spinae, the Erector Spinae and a muscle in the front portion of the subject's thigh, or the Deltoid, Erector Spinae and Vastus Lateralis. A large number of Functional Activities can be monitored using these featured muscles.
According to a further feature, the method includes the step of transmitting data representing the Functional Activities of the test subject between a location occupied thereby and a remote location for evaluation by testing personnel. This feature facilitates monitoring of a test subject by remotely located testing personnel.
According to an additional feature of the invention, the algorithm includes a Neural Network or Fuzzy Logic technique both of which are particularly effective in establishing useful data bases.
Accord
DeLuca Carlo J.
Roy Serge H.
Altec, Inc.
Astorino Michael C.
Jarcho Harold G.
Shaver Kevin
Toupal John E.
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