Accelerometry-based motion analysis is widely recognized as a promising tool in health care and medical settings since it is unobtrusive, inexpensive, and capable of providing useful information on human movement disorders. Patients suffering from neurological diseases such as Parkinson's disease (PD) often exhibit a combination of multiple motion symptoms during everyday activities. Thus, there is a need in clinical practice to capture as many types of abnormal movements as possible with minimal instrumentation that does not interfere with the subject's usual behavioral patterns. This paper presents the prospect of total health monitoring with a single accelerometer-based technique. The behavior of a PD patient was continuously recorded for a period of 36 h using a portable device with a triaxial accelerometer worn on the waist. Data were analyzed by newly developed computer programs to extract relevant movement parameters that might underlie pathological motor performance. We found that the state of the disease could be quantified in terms of distinctive aspects such as gait force, synchronization between both legs, and falls during diurnal walking, and turnover and respiration during nocturnal sleep. Our method may be a useful and practical tool that enables refined clinical assessment of the overall health status of patients with motion disorders.
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Yoneyama et al. (2013) studied this question.
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