Abstract
This paper presents a design of new type of multi-parameter wearable medical devices signal processing platform. The signal processing algorithm has a QRS-wave detection algorithm based on LADT, wavelet transformation and threshold detection with TMS320VC5509 DSP system. The DSP can greatly increase the speed of QRS-wave detection, and the results can be practical used for multi-parameter wearable device detection of abnormal ECG.
Highlights
The multi-parameter wearable medical devices have physiological signal detection and processing modules, signal feature extraction and data transmission basic function modules which can implement a non-invasive detection and diagnosis on the human body
This paper presents a design of new type of multi-parameter wearable medical devices signal processing platform
The signal processing algorithm has a QRS-wave detection algorithm based on linear approximation distance thresholding (LADT), wavelet transformation and threshold detection with TMS320VC5509 DSP system
Summary
The multi-parameter wearable medical devices have physiological signal detection and processing modules, signal feature extraction and data transmission basic function modules which can implement a non-invasive detection and diagnosis on the human body. It generally has the characteristics of removable operation, easy to use, support long time of continuous work, the intellectualized display diagnostic results, abnormal physiological condition alarms and wireless data transmission, etc. In the ECG signal analysis process, the QRS-wave detection is the most important issue. The drawback of use software (such as C++, Java) to implement the LADT algorithm is slower on the PC; this way can be used for algorithm simulation, so the general-purpose computer system with special accelerated processor were a feasible solution. This paper describes the structure of a multi-parameter monitoring module based on DSP chip solutions of hardware architecture and software components
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