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ReserarchID
WHE5B
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Health monitoring, nowadays become very crucial to tackle huge populations health hazards as technological development is ever upbringing that gives opportunity to help people catering for many health risks in easy way. Nowadays health monitoring is a very crucial research field to address huge population health hazards in effective ways using technologies because availability of human health care personnel are inadequate and costly. Accidental fall is one of the common health risk which leads to severe health injuries, even some cases results in death especially for elderly people (> 65 years old). With the help of wearable sensor system (WSS) many fall detection studies take place to minimize the health injuries; however the studies cannot provide expected efficient result. In this study we have proposed a novel technique to identify successfully fall detection and avoid misclassification using accelerometer and ECG sensors. Analyzing both critical physical movement and mental stress, which are evaluated from the signals of accelerometer and ECG sensors respectively, fall detection process can be greatly enhanced.
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