Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/28271
Author(s): Postolache, O.
Editor: Miclaus, S., Bechet, P., Munteanu, M., and Dan Milici, L.
Date: 2022
Title: Smart sensing and AI for physical therapy in IoT era
Volume: 1254
Book title/volume: IOP Conference Series: Materials Science and Engineering
Event title: International Conference on Electromagnetic Fields, Signals and BioMedical Engineering (ICEMS-BIOMED 2022)
Reference: Postolache, O. (2022). Smart sensing and AI for physical therapy in IoT era. In S. Miclaus, P. Bechet, M. Munteanu, & L. Dan Milici (Eds.), IOP Conference Series: Materials Science and Engineering (vol. 1254). IOP Publishing. https://doi.org/10.1088/1757-899X/1254/1/012006
ISSN: 1757-8981
DOI (Digital Object Identifier): 10.1088/1757-899X/1254/1/012006
Abstract: It is well known that medical spending increase with disability status. Per capita spending for people with five or more limitations in activities of daily living (ADLs) is nearly five times the amount incurred by those with limitations in only one instrumental activities of daily living (IADLs). Physical therapy is the way to improve the motor capabilities however it takes a lot of time, it requires physiotherapists services, is often painful and the outcome are evaluated in subjective way. New technologies including smart sensors were adopted in healthcare including wearable solutions for cardiac and respiratory activity monitoring and successfully are contributing to reduce the costs of services. In the case of motor activity and particularly in physical rehabilitation the developments are still reduced the physical therapy services are using as hardware mechanical equipment without sensing, embedded processing and internet connectivity that significatively reduce the possibility to measure and evaluate the physical training outcomes in objective way. In this paper the disruptive solutions for physical therapy are presented that are based on hot technologies such as smart sensors, IoT, virtual reality (VR), mixed reality (MR), and artificial intelligence (AI). Applied AI may conduct to develop models, classifiers (gait classification) and short term or medium term prediction of physical therapy outcomes. Highly motivation of the patients under physical rehabilitation can be increased promoting serious game characterized by VR and MR scenarios
Peerreviewed: yes
Access type: Open Access
Appears in Collections:IT-CRI - Comunicações a conferências internacionais

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