Accelerometers in Rehabilitation
Original Editor - Ananya Bunglae Sudindar
Top Contributors - Ananya Bunglae Sudindar
Introduction[edit | edit source]
Wearable devices, also known as wearables, are instruments that have garnered significant attention for enabling non-invasive, real-time monitoring of physical and physiological parameters in smart care and digital medicine. These devices are worn on the body and provide physiological measures directly to smart devices, offering valuable insights into health metrics. [1][2][3]
Accelerometers are wearable devices designed to measure the acceleration of the body segment to which they are attached[4]. These devices play a crucial role in studying human movement across various applications, including activity detection, assessing postural balance, evaluating sports physical function, and investigating falls. They operate based on Newton’s law of motion wherein they measure linear acceleration which represents the change in an object’s speed over time. [5]
Application in Rehabilitation[edit | edit source]
Placement on Body Segments[edit | edit source]
Advantages of Accelerometers[edit | edit source]
References[edit | edit source]
- ↑ Miller DJ, Sargent C, Roach GD. A validation of six wearable devices for estimating sleep, heart rate and heart rate variability in healthy adults. Sensors. 2022 Aug 22;22(16):6317.
- ↑ Lu L, Zhang J, Xie Y, Gao F, Xu S, Wu X, Ye Z. Wearable health devices in health care: narrative systematic review. JMIR mHealth and uHealth. 2020 Nov 9;8(11):e18907.
- ↑ Lin WY, Chen CH, Lee MY. Design and implementation of a wearable accelerometer-based motion/tilt sensing internet of things module and its application to bed fall prevention. Biosensors. 2021 Oct 29;11(11):428.
- ↑ Migueles JH, Cadenas-Sanchez C, Ekelund U, Delisle Nyström C, Mora-Gonzalez J, Löf M, Labayen I, Ruiz JR, Ortega FB. Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations. Sports medicine. 2017 Sep;47:1821-45.
- ↑ Celik Y, Vitorio R, Powell D, Moore J, Young F, Coulby G, Tung J, Nouredanesh M, Ellis R, Izmailova ES, Stuart S. Sensor Integration for Gait Analysis.
