In this paper, compressed sensing based fall detection system for elderly using WSN (CSFDS) is proposed. Since the multimedia data requires high bandwidth, there is a need for efficient compression. In this framework, fall frames are identified from a monitored video and transmitted using wireless sensor nodes. A sudden fall has to be informed to the caretaker immediately and wireless sensor networks are capable of sensing these falls. Falls are one of the unpredicted but hazardous events. As the number of elderly person is increasing, home monitoring for healthcare applications is playing a vital role in our daily life. Recent researches have pointed out that one third persons are aged 65 and above requires special health care. Experimental results show that the presented system design achieves better video quality than traditional video coding and transmission scheme, while the requirement for a low-cost, noninvasive and real-time healthcare monitoring system is accommodated. After video compression and transmission over a wireless sensor network, the remote receiver recovered the videos and performed multi-view motion capture for gait analysis. In the scenario, the subject walked on a treadmill with four tripod cameras capturing the video from different viewpoints. Second, all components are seamlessly integrated in a unified optimization framework dedicated for online data transmission. First, several novel ideas are developed, including fast object detection, and content-aware and adaptive video coding and transmission. The major components include video capture, object detection, video coding and transmission, error concealment, and video analysis. This paper presents a multi-camera motion capture system aiming to provide caregivers with timely access to the patient's health status through mobile communication devices.

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