A Wearable Inertial Measurement Unit for Long-Term Monitoring in the Dependency Care Area

TLDR

Human movement analysis, enabled by wearable inertial measurement units, is widely studied for assessing quality‑of‑life variables and can be processed offline or in real time. The paper introduces a sensor system that simultaneously records and processes movement data in real time. The platform integrates a triaxial accelerometer, gyroscope, magnetometer, optional additional sensors, µSD storage, and Bluetooth for data acquisition and transmission. It has been applied to real‑time detection of Parkinson’s disease symptoms, gait analysis, and fall detection.

Abstract

Human movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with long battery life. The IMU's movement signals might be, on the one hand, stored in a digital support, in which an analysis is performed a posteriori. On the other hand, the signal analysis might take place in the same IMU at the same time as the signal acquisition through online classifiers. The new sensor system presented in this paper is designed for both collecting movement signals and analyzing them in real-time. This system is a flexible platform useful for collecting data via a triaxial accelerometer, a gyroscope and a magnetometer, with the possibility to incorporate other information sources in real-time. A µSD card can store all inertial data and a Bluetooth module is able to send information to other external devices and receive data from other sources. The system presented is being used in the real-time detection and analysis of Parkinson's disease symptoms, in gait analysis, and in a fall detection system.