Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Engineering
Development Of A Wireless Mobile Computing Platform For Fall Risk Prediction, Akm Jahangir Alam Majumder
Development Of A Wireless Mobile Computing Platform For Fall Risk Prediction, Akm Jahangir Alam Majumder
Dissertations (1934 -)
Falls are a major health risk with which the elderly and disabled must contend. Scientific research on smartphone-based gait detection systems using the Internet of Things (IoT) has recently become an important component in monitoring injuries due to these falls. Analysis of human gait for detecting falls is the subject of many research projects. Progress in these systems, the capabilities of smartphones, and the IoT are enabling the advancement of sophisticated mobile computing applications that detect falls after they have occurred. This detection has been the focus of most fall-related research; however, ensuring preventive measures that predict a fall is …
Lpcoms: Towards A Low Power Wireless Smart-Shoe System For Gait Analysis In People With Disabilities, Ishmat Zerin
Lpcoms: Towards A Low Power Wireless Smart-Shoe System For Gait Analysis In People With Disabilities, Ishmat Zerin
Master's Theses (2009 -)
Gait analysis using smart sensor technology is an important medical diagnostic process and has many applications in rehabilitation, therapy and exercise training. In this thesis, we present a low power wireless smart-shoe system (LPcomS) to analyze different functional postures and characteristics of gait while walking. We have designed and implemented a smart-shoe with a Bluetooth communication module to unobtrusively collect data using smartphone in any environment. With the design of a shoe insole equipped with four pressure sensors, the foot pressure is been collected, and those data are used to obtain accurate gait pattern of a patient. With our proposed …