An Environmental-Adaptive Fall Detection System on Mobile Device

Abstract

When facing damages caused by falls, a well designed smart sensor system to detect falls can be both medically and economically helpful. This research introduces a portable terrain adaptable fall detection system, by placing accelerometers and gyroscopes in parts of the body and transmit data through wireless transmitter modules to mobile devices to get the related information and combining it with the center of gravity clustering algorithm introduced in this research which computes the human body behavior patterns according the relationship between the center of gravity in the body and the feet portion of the body. Compared with the research in the past, this system is not only highly accurate and robust, but also able to adapt to different types of terrains, which solves the problems that other researches have for detection errors when the client is climbing the stairs or walking on a slant.

Detecting Falls with Wearable Sensors Using Machine Learning Techniques

“…The algorithms can be easily embedded into portable devices or accessories carried on the body that can be connected to a telephone network [34]. This feature will allow prompt medical attention, improve the safety, independence, and quality of living of those in fall risk groups, and contribute to the economy by reducing the costs of medical healthcare.…”

Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues

“…Some solutions use both SP sensors and external sensors for detection and prediction of falls events [29,30]. It is also possible to use SPs for analysis and/or communication but not for sensing [31,32]. An uncommon type of solution was proposed by Hansen et al [21].…”

“…Body-worn systems can also use external sensing and processing units together with SPs to overcome these two constraints. Some of these external units are used only for sensing or measuring physical quantities [31,32]. These units will transmit raw data to the SP, and then the SP will perform feature extraction, classification and notification tasks.…”

“…The most important feature, that is not included in these articles, is the performance or the correctness of the reviewed solutions. More than half of the articles [2,21,26,27,29,32,34,43,45,54,55,57,65,70,71,73,74,77,79,82,85,89,91,93–95] do not declare the performance/accuracy of their systems, because these articles present very preliminary investigations on SP-based fall detection and fall prevention. The remaining articles, included in Table 5, discussed the performance of their proposed solutions but there were major differences between the evaluation techniques.…”

Wearable Inertial Sensors and Their Applications

“…A portable triaxial accelerometer attached at the shoulder was used to monitor the severity of the dyskinesia, which occurs as an uncomfortable side effect of PD medication. The acceleration signal and severity of the dyskinesia are highly correlated [60].…”