A Low-Cost Point-of-Care Testing System for Psychomotor Symptoms of Depression Affecting Standing Balance: A Preliminary Study in India
Author(s) -
Arindam Dutta,
Robins Kumar,
Suruchi Malhotra,
Sanjay Chugh,
Alakananda Banerjee,
Anirban Dutta
Publication year - 2013
Publication title -
depression research and treatment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.738
H-Index - 27
eISSN - 2090-133X
pISSN - 2090-1321
DOI - 10.1155/2013/640861
Subject(s) - psychomotor learning , depression (economics) , medicine , psychomotor retardation , balance (ability) , psychological intervention , quality of life (healthcare) , physical therapy , physical medicine and rehabilitation , gerontology , psychiatry , cognition , alternative medicine , nursing , pathology , economics , macroeconomics
The World Health Organization estimated that major depression is the fourth most significant cause of disability worldwide for people aged 65 and older, where depressed older adults reported decreased independence, poor health, poor quality of life, functional decline, disability, and increased chronic medical problems. Therefore, the objectives of this study were (1) to develop a low-cost point-of-care testing system for psychomotor symptoms of depression and (2) to evaluate the system in community dwelling elderly in India. The preliminary results from the cross-sectional study showed a significant negative linear correlation between balance and depression. Here, monitoring quantitative electroencephalography along with the center of pressure for cued response time during functional reach tasks may provide insights into the psychomotor symptoms of depression where average slope of the Theta-Alpha power ratio versus average slope of baseline-normalized response time may be a candidate biomarker, which remains to be evaluated in our future clinical studies. Once validated, the biomarker can be used for monitoring the outcome of a comprehensive therapy program in conjunction with pharmacological interventions. Furthermore, the frequency of falls can be monitored with a mobile phone-based application where the propensity of falls during the periods of psychomotor symptoms of depression can be investigated further.
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