Literature DB >> 22155937

Noncontact tremor characterization using low-power wideband radar technology.

Gaddi Blumrosen1, Moshe Uziel, Boris Rubinsky, Dana Porrat.   

Abstract

Continuous monitoring and analysis of tremor is important for the diagnosis and establishment of treatments in many neurological disorders. This paper describes noncontact assessment of tremor characteristics obtained by an experimental new ultrawideband (UWB) system. The system is based on transmission of a wideband electromagnetic signal with extremely low power, and analysis of the received signal, which is composed of many propagation paths reflected from the patient and its surroundings. A description of the physical principles behind the technology, a criterion, and efficient algorithms to assess tremor characteristics from the bulk UWB measurements are given. A feasibility test for the technology was conducted using a UWB system prototype, an arm model that mimics tremor, and a reference video system. The set of UWB system frequencies and amplitudes estimations were highly correlated with the video system estimations with an average error in the scale of 0.1 Hz and 1 mm for the frequency and amplitude estimations, respectively. The new UWB-based system does not require attaching active markers or inertial sensors to the body, can give displacement information and kinematic features from multiple body parts, is not limited by the range captured by the optical lens, has high indoor volume coverage as it can penetrate through walls, and does not require calibration to obtain amplitude estimations.

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Year:  2011        PMID: 22155937     DOI: 10.1109/TBME.2011.2177977

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  3 in total

1.  A Real-Time Kinect Signature-Based Patient Home Monitoring System.

Authors:  Gaddi Blumrosen; Yael Miron; Nathan Intrator; Meir Plotnik
Journal:  Sensors (Basel)       Date:  2016-11-23       Impact factor: 3.576

2.  Human body parts tracking and kinematic features assessment based on RSSI and inertial sensor measurements.

Authors:  Gaddi Blumrosen; Ami Luttwak
Journal:  Sensors (Basel)       Date:  2013-08-23       Impact factor: 3.576

3.  Radar based technology for non-contact monitoring of accumulation of blood in the head: A numerical study.

Authors:  Moshe Oziel; Rafi Korenstein; Boris Rubinsky
Journal:  PLoS One       Date:  2017-10-12       Impact factor: 3.240

  3 in total

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