Accelerometers in Rehabilitation: Difference between revisions
(added headings) |
No edit summary |
||
| Line 11: | Line 11: | ||
== Application in Rehabilitation == | == Application in Rehabilitation == | ||
==== Gait Analysis ==== | |||
The application of accelerometers in gait analysis is a transformative practice that spans a spectrum of clinical domains, ranging from orthopedic and neurological disorders to cardiovascular issues. These motion sensors, primarily accelerometers, are strategically positioned on various body parts, including the ear, shank, thigh, pelvis, and foot, to capture and assess the spatio-temporal parameters of an individual's walking pattern. The accelerometers record accelerations and decelerations during movement, generating invaluable data that sheds light on crucial gait characteristics such as symmetry, balance, stride length, step frequency, and temporal aspects. | |||
This comprehensive approach often involves the simultaneous use of multiple accelerometers to obtain a holistic understanding of the entire body's movement dynamics. Triaxial accelerometers, capturing movement in three dimensions, play a pivotal role by providing detailed insights into motion across the frontal, sagittal, and transverse planes. | |||
Moreover, the tailored application of accelerometers in gait analysis proves particularly beneficial in addressing specific conditions such as Parkinson's disease, Huntington's disease, cerebral palsy, and orthopedic injuries. For instance, in Parkinson's disease, the focus is on detecting freezing of gait (FoG) and other abnormalities, showcasing the adaptability and precision of this technology. | |||
The insights derived from gait analysis with accelerometers not only contribute to accurate diagnosis but also play a crucial role in treatment planning and the formulation of effective rehabilitation strategies. In essence, the use of accelerometers in gait analysis emerges as a versatile and indispensable tool in clinical practice, offering nuanced insights into the intricate dynamics of human movement.<ref>Jarchi D, Pope J, Lee TK, Tamjidi L, Mirzaei A, Sanei S. [https://core.ac.uk/reader/159754535?utm_source=linkout A review on accelerometry-based gait analysis and emerging clinical applications.] IEEE reviews in biomedical engineering. 2018 Feb 16;11:177-94.</ref> | |||
==== Monitoring Physical Activity Levels ==== | |||
==== Tracking Movement Patterns ==== | |||
== Placement on Body Segments == | == Placement on Body Segments == | ||
== Advantages of Accelerometers == | == Advantages of Accelerometers == | ||
* 1 | |||
* 2 | |||
== References == | == References == | ||
<references /> | <references /> | ||
Revision as of 17:46, 23 November 2023
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]
Gait Analysis[edit | edit source]
The application of accelerometers in gait analysis is a transformative practice that spans a spectrum of clinical domains, ranging from orthopedic and neurological disorders to cardiovascular issues. These motion sensors, primarily accelerometers, are strategically positioned on various body parts, including the ear, shank, thigh, pelvis, and foot, to capture and assess the spatio-temporal parameters of an individual's walking pattern. The accelerometers record accelerations and decelerations during movement, generating invaluable data that sheds light on crucial gait characteristics such as symmetry, balance, stride length, step frequency, and temporal aspects.
This comprehensive approach often involves the simultaneous use of multiple accelerometers to obtain a holistic understanding of the entire body's movement dynamics. Triaxial accelerometers, capturing movement in three dimensions, play a pivotal role by providing detailed insights into motion across the frontal, sagittal, and transverse planes.
Moreover, the tailored application of accelerometers in gait analysis proves particularly beneficial in addressing specific conditions such as Parkinson's disease, Huntington's disease, cerebral palsy, and orthopedic injuries. For instance, in Parkinson's disease, the focus is on detecting freezing of gait (FoG) and other abnormalities, showcasing the adaptability and precision of this technology.
The insights derived from gait analysis with accelerometers not only contribute to accurate diagnosis but also play a crucial role in treatment planning and the formulation of effective rehabilitation strategies. In essence, the use of accelerometers in gait analysis emerges as a versatile and indispensable tool in clinical practice, offering nuanced insights into the intricate dynamics of human movement.[6]
Monitoring Physical Activity Levels[edit | edit source]
Tracking Movement Patterns[edit | edit source]
Placement on Body Segments[edit | edit source]
Advantages of Accelerometers[edit | edit source]
- 1
- 2
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.
- ↑ Jarchi D, Pope J, Lee TK, Tamjidi L, Mirzaei A, Sanei S. A review on accelerometry-based gait analysis and emerging clinical applications. IEEE reviews in biomedical engineering. 2018 Feb 16;11:177-94.
