Abstract
Quantitative indoor monitoring, in a low-invasive and accurate way, is still an unmet need in clinical practice. Indoor environments are more challenging than outdoor environments, and are where patients experience difficulty in performing activities of daily living (ADLs). In line with the recent trends of telemedicine, there is an ongoing positive impulse in moving medical assistance and management from hospitals to home settings. Different technologies have been proposed for indoor monitoring over the past decades, with different degrees of invasiveness, complexity, and capabilities in full-body monitoring. The major classes of devices proposed are inertial-based sensors (IMU), vision-based devices, and geomagnetic and radiofrequency (RF) based sensors. In recent years, among all available technologies, there has been an increasing interest in using RF-based technology because it can provide a more accurate and reliable method of tracking patients’ movements compared to other methods, such as camera-based systems or wearable sensors. Indeed, RF technology compared to the other two techniques has higher compliance, low energy consumption, does not need to be worn, is less susceptible to noise, is not affected by lighting or other physical obstacles, has a high temporal resolution without a limited angle of view, and fewer privacy issues. The aim of the present narrative review was to describe the potential applications of RF-based indoor monitoring techniques and highlight their differences compared to other monitoring technologies.
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference191 articles.
1. Overview of recent development on wireless sensing circuits and systems for healthcare and biomedical applications;Li;IEEE J. Emerg. Sel. Top. Circuits Syst.,2018
2. New methods for the assessment of Parkinson’s disease (2005 to 2015): A systematic review;Sánchez-Ferro;Mov. Disord.,2016
3. Summa, S., Tosi, J., Taffoni, F., Di Biase, L., Marano, M., Rizzo, A.C., Tombini, M., Di Pino, G., and Formica, D. Assessing bradykinesia in Parkinson’s disease using gyroscope signals. Proceedings of the 2017 International Conference on Rehabilitation Robotics (ICORR), 2017.
4. Quantitative Analysis of Bradykinesia and Rigidity in Parkinson’s Disease;Di Biase;Front. Neurol.,2018
5. PDMeter: A Wrist Wearable Device for an at-home Assessment of the Parkinson’s Disease Rigidity;Raiano;IEEE Trans. Neural Syst. Rehabil. Eng.,2020
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献