Merryn Mathie

Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring

The real-time monitoring of human movement can provide valuable information regarding an individuals degree of functional ability and general level of activity. This paper presents the implementation of a real-time classification system for the types of human movement associated with the data acquired from a single, waist-mounted triaxial accelerometer unit. The major advance proposed by the system is to perform the vast majority of signal processing onboard the wearable unit using embedded intelligence. In this way, the system distinguishes between periods of activity and rest, recognizes the postural orientation of the wearer, detects events such as walking and falls, and provides an estimation of metabolic energy expenditure. A laboratory-based trial involving six subjects was undertaken, with results indicating an overall accuracy of 90.8% across a series of 12 tasks (283 tests) involving a variety of movements related to normal daily activities. Distinction between activity and rest was performed without error; recognition of postural orientation was carried out with 94.1% accuracy, classification of walking was achieved with less certainty (83.3% accuracy), and detection of possible falls was made with 95.6% accuracy. Results demonstrate the feasibility of implementing an accelerometry-based, real-time movement classifier using embedded intelligence

Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement

Accelerometry offers a practical and low cost method of objectively monitoring human movements, and has particular applicability to the monitoring of free-living subjects. Accelerometers have been used to monitor a range of different movements, including gait, sit-to-stand transfers, postural sway and falls. They have also been used to measure physical activity levels and to identify and classify movements performed by subjects. This paper reviews the use of accelerometer-based systems in each of these areas. The scope and applicability of such systems in unsupervised monitoring of human movement are considered. The different systems and monitoring techniques can be integrated to provide a more comprehensive system that is suitable for measuring a range of different parameters in an unsupervised monitoring context with free-living subjects. An integrated approach is described in which a single, waist-mounted accelerometry system is used to monitor a range of different parameters of human movement in an unsupervised setting.

Classification of basic daily movements using a triaxial accelerometer.

A generic framework for the automated classification of human movements using an accelerometry monitoring system is introduced. The framework was structured around a binary decision tree in which movements were divided into classes and subclasses at different hierarchical levels. General distinctions between movements were applied in the top levels, and successively more detailed subclassifications were made in the lower levels of the tree. The structure was modular and flexible: parts of the tree could be reordered, pruned or extended, without the remainder of the tree being affected. This framework was used to develop a classifier to identify basic movements from the signals obtained from a single, waist-mounted triaxial accelerometer. The movements were first divided into activity and rest. The activities were classified as falls, walking, transition between postural orientations, or other movement. The postural orientations during rest were classified as sitting, standing or lying. In controlled laboratory studies in which 26 normal, healthy subjects carried out a set of basic movements, the sensitivity of every classification exceeded 87%, and the specificity exceeded 94%; the overall accuracy of the system, measured as the number of correct classifications across all levels of the hierarchy, was a sensitivity of 97.7% and a specificity of 98.7% over a data set of 1309 movements.

Detection of daily physical activities using a triaxial accelerometer

Triaxial accelerometers have been employed to monitor human movements in a variety of circumstances. The study considered the use of data from a single waist-mounted triaxial accelerometer to distinguish between activity states and rest. A method using acceleration magnitude was applied to data collected from 26 normal subjects performing sit-to-stand and stand-to-sittransitions and walking. The effects of three parameters were investigated: the length n of a smoothing median filter, the width w of the averaging window used to process the signal and the value of the acceleration magnitude threshold th. These were found to be inter-related, and sets of parameters that resulted in accurate discrimination were determined by the relationship between th and the product of w and n, and by the relationship between n and w. The subjects were randomly divided into control (N=13) and test (N=13) groups. Optimum parameter sets were determined using the control group. Eleven sets of parameters yielded the same optimum results of a sensitivity of 1.0 and a specificity of 0.96 in the control group. Upon application to the test group, using these parameters, the system successfully distinguished between activity and rest, giving sensitivities greater than 0.98 and specificities between 0.88 and 0.94.

A pilot study of long-term monitoring of human movements in the home using accelerometry

We assessed the feasibility of using a waist-mounted, wireless triaxial accelerometer (TA) to monitor human movements in an unsupervised home setting to detect changes in functional status. A pilot study was carried out with six healthy subjects aged 80–86 years. The subjects wore a TA unit every day for two to three months. Each morning they carried out a short routine of directed movements that included standing, sitting, lying and walking. Important movement variables were measured. During the rest of the day, subjects were monitored for falls, and variables such as metabolic energy expenditure were measured. All subjects remained healthy; there was no overall change in functional status and there were only slight fluctuations in health status. No longitudinal changes were detected in any of the variables measured during the directed routine. There was a moderate correlation between weekly self-reported health status and energy expenditure: subjects reported a lower health status for weeks in which they expended less energy. The TA system was found to be practical for long-term, unsupervised home monitoring. All subjects found the system simple to use and the TA unit unobtrusive and comfortable to wear. High compliance rates were achieved: the TA units were worn on 88% of the days in the study, for an average of 11.2 hours per day.

A system for monitoring posture and physical activity using accelerometers

Advances in technology have made possible new and innovative methods of health care delivery. Home telecare, in which the patients health is monitored remotely at home, is one such method. This paper discusses the use of a triaxial accelerometer within a home telecare system for monitoring physiological and functional parameters for daily living. A novel system is described for objectively and continuously monitoring movement, suitable for patients with chronic diseases including congestive heart failure and chronic obstructive pulmonary disease. The key design criteria were ease of use by, and comfort for, the patient together with the provision of clinically relevant information. The patients posture, energy expenditure and movement are clinically important parameters that can be measured by accelerometry. A data processing scheme in which these parameters are extracted is described.

Determining activity using a triaxial accelerometer

Triaxial accelerometers have been employed to monitor human movements in a variety of circumstances. It is necessary, however, to be able to extract useful information from the acceleration measurements. We show that we can, in a controlled environment, use an energy expenditure method to identify and separate dynamic activities, including changes in posture and ambulation.

Managing chronic disease with home telecare: a system architecture and case study

An overview of the system architecture of a home telecare system (HTS) that was successfully deployed in city and rural Australia Is presented. We describe a case study from a patient with chronic obstructive pulmonary disease who was monitored in her home for a six-month period. A summary of patient and clinician responses to initial and final evaluation questionnaires is presented. There was generally a high level of acceptance of the HTS with both patients and their general practitioners responding favorably on its ease of use, effectiveness and likely impact on improving management of chronic disease.

Home telecare for chronic disease management

We review the development of an Internet-enabled home clinical workstation for the management of chronic disease, and the implementation of a clinical trial to test the functionality, usability and effectiveness of the system in both a city and a remote country setting. The Home Telecare System integrates with established primary care services to provide a new paradigm of active disease management through the daily collection of clinical data and assessment of functional health status, and the provision of feedback for patient self-management and education. A novel Medications Management module is also implemented to permit on line variation of prescribed medications.