Portable gait analysis sensor model for Parkinson's disease. (2022)

• Record Type: Journal Article
• Authors: Piromalis, Dimitrios; Kounelis, Marios; Kolovos, Dimitrios P.; Kokkotis, Christos; Tsatalas, Themistoklis; Bellis, George; Tsaopoulos, Dimitrios; Giakas, Giannis; Chronakis, Antonis; Koutsouraki, Eleni; Tsotsolas, Nikos; Randhawa, Princy; Patel, Akshet
• Is Part Of: Materials today. Volume 63:(2022)
• Page Start: 653
• Page End: 662
• Publication Date: 2022
• Subjects: Parkinson's disease -- Wearable devices -- Firmware -- Monitoring technologies -- Gait analysis -- Embedded systems -- Data acquisition systems; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2022.04.724
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: As part of a research project, a small gait analysis device is being developed that will be used outside of home by the patients themselves. Its main purpose will be to record accurate gait measurements in patients with Parkinson's Disease and proceed with in-depth analysis of the gait characteristics. A key feature of the device will be its small size, which creates specific requirements in terms of device consumption restrictions due to the small size of the battery and the need for autonomous operation for more than ten hours. This research work describes, on the one hand, the firmware of the device with an emphasis on the functions that will be implemented; and, on the other, the device software which will support the process that will be adopted for reading and processing data from the devices placed on patients' feet to record the gait characteristics of patients on a continuous basis. Using these computational approaches, we developed and carried out an experiment with a 1.60 m tall experimental female subject. We strapped a device to the subject's right ankle and instructed her to take five steps with her right foot, turn 180 degrees, and repeat with the same foot.