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

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.

Remote control of apomorphine infusion rate in Parkinson's disease: Real-time dose variations according to the patients' motor state. A proof of concept

“…Intensive adjustment of the apomorphine dose, in response to patients' motor fluctuations, could be done either manually by the patient or automatically through the use of new technologies for detection of motor symptoms [3]. This study is a proof of concept which, despite limited results due to the small sample size, shows a tendency towards an improved symptom control (shorter time in Off; less rescues needed) during the intervention periods, where the dose was changed depending on the patient's motor state.…”

“…Furthermore, the technological development of sensors allows for the design of smaller and more wearable systems to detect motor fluctuations [3]. Such sensors can automatically detect the moments in which a patient needs more doses [4], thus allowing for automatic or semi-automatic control of the infusion pump.…”

Synchronous Wearable Wireless Body Sensor Network Composed of Autonomous Textile Nodes

“…In terms of complete on-body electronic systems, many rigid wearable nodes exist, often hindering the wearer's movements [9–12]. Many others also performed research on off-body antennas or body area radio propagation for sensor networks [13,14].…”

Detecting Elementary Arm Movements by Tracking Upper Limb Joint Angles With MARG Sensors

“…Some of the application scenarios considered are those of rehabilitation, chronic care management and elderly population monitoring [8]- [10], [21]- [24]. Typically, the data obtained are used to derive a set of features which are then used as inputs in various machine learning and/or pattern recognition systems for classification.…”