Next Article in Journal
Dynamic Uncertainty for Compensated Second-Order Systems
Next Article in Special Issue
A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring
Previous Article in Journal
Detecting Abnormal Vehicular Dynamics at Intersections Based on an Unsupervised Learning Approach and a Stochastic Model
Previous Article in Special Issue
A Piezoelectric Plethysmograph Sensor Based on a Pt Wire Implanted Lead Lanthanum Zirconate Titanate Bulk Ceramic
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Efficacy of a Computerized Sensor System for Evaluation and Training of Dizzy Patients

1
Department of Physical Medicine and Rehabilitation, Taipei Veterans General Hospital, 201 Shih-Pai, Road, Section 2, 11217, Taipei, Taiwan
2
School of Medicine, National Yang-Ming University, No. 155, Section 2, Linong Street, Taipei, 11221, Taiwan
3
Center for Geriatrics & Gerontology, Taipei Veterans General Hospital, 201 Shih-Pai Road, Section 2, 11217, Taipei, Taiwan
4
Institute of Physical Therapy and Assistive Technology, National Yang-Ming University, No. 155, Section 2, Linong Street, Taipei, 11221, Taiwan
5
Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, 201 Shih-Pai, Road, Section 2, 11217, Taipei, Taiwan
6
Department of Ophthalmology, Taipei Veterans General Hospital, 201 Shih-Pai, Road, Section 2, 11217, Taipei, Taiwan
*
Authors to whom correspondence should be addressed.
Sensors 2010, 10(8), 7602-7620; https://doi.org/10.3390/s100807602
Submission received: 28 May 2010 / Revised: 2 July 2010 / Accepted: 5 August 2010 / Published: 12 August 2010
(This article belongs to the Special Issue Sensors in Biomechanics and Biomedicine)

Abstract

Patients with vestibular hypofunction often experience dizziness and unsteadiness while moving their heads. Appropriate sensors can effectively detect a patient’s dynamic visual acuity and associated body balance control. Forty-one vestibular-deficit patients and 10 normal individuals were invited to participate in this study. Questionnaires, clinical assessment scales and objective measures were evaluated on participants’ first visits. After 12 sessions of training, all scales were evaluated again on vestibular-deficit patients. The computerized system was composed of sensors, including a gyro and strain gauges, data acquisition accessories and LabVIEW software. Results revealed that the system could effectively distinguish normal subjects from subjects with vestibular deficits. In addition, after a rehabilitation program, subjects’ subjective and objective performances were significantly improved. Based on our results, we concluded that the present system, which uses a gyro and strain gauges, may provide an effective method for assessing and treating vestibular-deficit patients.
Keywords: dizziness; balance; dynamic visual acuity; center of pressure; vestibular hypofunction dizziness; balance; dynamic visual acuity; center of pressure; vestibular hypofunction

Share and Cite

MDPI and ACS Style

Kao, C.-L.; Hsieh, W.-L.; Wang, S.-J.; Chen, S.-J.; Wei, S.-H.; Chan, R.-C. Efficacy of a Computerized Sensor System for Evaluation and Training of Dizzy Patients. Sensors 2010, 10, 7602-7620. https://doi.org/10.3390/s100807602

AMA Style

Kao C-L, Hsieh W-L, Wang S-J, Chen S-J, Wei S-H, Chan R-C. Efficacy of a Computerized Sensor System for Evaluation and Training of Dizzy Patients. Sensors. 2010; 10(8):7602-7620. https://doi.org/10.3390/s100807602

Chicago/Turabian Style

Kao, Chung-Lan, Wan-Ling Hsieh, Shuu-Jiun Wang, Shih-Jen Chen, Shun-Hwa Wei, and Rai-Chi Chan. 2010. "Efficacy of a Computerized Sensor System for Evaluation and Training of Dizzy Patients" Sensors 10, no. 8: 7602-7620. https://doi.org/10.3390/s100807602

APA Style

Kao, C.-L., Hsieh, W.-L., Wang, S.-J., Chen, S.-J., Wei, S.-H., & Chan, R.-C. (2010). Efficacy of a Computerized Sensor System for Evaluation and Training of Dizzy Patients. Sensors, 10(8), 7602-7620. https://doi.org/10.3390/s100807602

Article Metrics

Back to TopTop