Feasibility study of filtering algorithms for low cost wireless physiological monitoring system

An increasing number of patients, high cost, lack of mobility, isolation from professional environment, among others issues demand a technology in which a patient should be monitored from home instead of hospital. This will force the development of more cost-effective and advanced wireless telemedicine solutions. The parameters like types of input (i.e. ECG, blood pressure, body temperature, etc.), sampling rate, distance between wireless modules, number of sensors connected in wireless network, adaptability of algorithms for signal processing, size of the device and power consumption can affect the performance and cost of the systems. This paper illustrates hardware for wireless ECG system and the performance of various algorithms applied to ECG received wirelessly in the standing and sitting position of patient; and with different sampling frequencies to meet the requirements of system low cost and easily adaptability. To demonstrate the work, a prototype of ECG front end is developed, tested and interfaced with Bluetooth module which digitizes the analog ECG signal and transmits the signal wirelessly to Bluetooth enabled devices. The algorithms like piecewise moving average, moving average, and S-Golay algorithm are implemented on the captured ECG with different sampling frequencies and with different positions of patient; and are compared. A template for moving average and piecewise algorithms is written in Microsoft (MS) Excel and tested for real time data update. The proposed system has successfully used the Bluetooth technology to transmit and receive physical signals along with testing of operational features of transmitting device through the air. The results show that a novel algorithm is required which can efficiently remove high frequency noise in any physical condition of patient and can be easily implemented in existing Mobile/PDA/Laptop, etc. to meet the system requirement of low cost and adaptability.