We have developed an automated surveillance system based on passive infra-red sensors. Eight sensors were installed in a hospital room. A computer automatically captured data from the sensors every night from 21:00 until 06:00 the following morning. The sensors were polled twice per second and when a sensor was activated by movement, the event and time were recorded in a data file. At the end of the surveillance period the program analysed the data and generated a report showing the activities taking place in the room and their times. Four elderly patients were observed for a total of 97 nights. A total of 1637 possible sequences of movements by the patient and the hospital staff were detected. The computer was able to identify 1450 sequences (89%) correctly, in comparison with manual analysis. Only 10 movements (0.6%) were undetected by the system; all were very short sequences (five or six activations of the sensors). The system was generally capable of detecting and classifying all major movements in the room.
A case study has been conducted in India to estimate the impact of Internet on delivery of critical health care. Time series data on discharge and death from intensive cardiac care units have been collected from three individual centers that are under the Internet based telemedicine project of a private public partnership. Logistic Regression analysis has been performed to estimate the response parameters and test of hypotheses. The results confirm the effectiveness of using Internet in providing critical cardiac care to patients. The findings can be utilized to increase the number of local telemedicine centers in remote and underdeveloped areas.
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