Accelerometry-Based Gait Analysis and Its Application to Parkinson's Disease Assessment- Part 2 : A New Measure for Quantifying Walking Behavior

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 21; no. 6; pp. 999 - 1005
• Main Authors: Yoneyama, Mitsuru, Kurihara, Yosuke, Watanabe, Kajiro, Mitoma, Hiroshi
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2013; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceleration; Accelerometers; Actigraphy - methods; Aged; biomedical signal processing; Diagnosis, Computer-Assisted - methods; Female; Gait; gait analysis; Gait Disorders, Neurologic - diagnosis; Gait Disorders, Neurologic - etiology; Gait Disorders, Neurologic - physiopathology; Humans; Male; Monitoring; Parkinson Disease - complications; Parkinson Disease - diagnosis; Parkinson Disease - physiopathology; Parkinson's disease; Parkinson's disease (PD); Patients; Rehabilitation; Reproducibility of Results; Sensitivity and Specificity; Severity of Illness Index; Walking
• ISSN: 1534-4320; 1558-0210; 1558-0210
• DOI: 10.1109/TNSRE.2013.2268251

Gait analysis is a valuable tool for obtaining quantitative information on motor deficits in Parkinson's disease (PD). Since the characteristic gait patterns of PD patients may not be fully identified by brief examination in a clinic, long-term, and unobtrusive monitoring of their activities is essential, especially in a nonclinical setting. This paper describes a single accelerometer-based gait analysis system for the assessment of ambulatory gait properties. Acceleration data were recorded continuously for up to 24 h from normal and PD subjects, from which gait peaks were picked out and the relationship between gait cycle and vertical gait acceleration was evaluated. By fitting a model equation to the relationships, a quantitative index was obtained for characterizing the subjects' walking behavior. The averaged index for PD patients with gait disorder was statistically smaller than the value for normal subjects. The proposed method could be used to evaluate daily gait characteristics and thus contribute to a more refined diagnosis and treatment of the disease.