The application background of physiological signal research focuses on education and research in the fields of life sciences, clinical diagnosis and monitoring applications, and is an important content in the field of biomedical engineering. The development and use of intelligent physiological signal acquisition systems have also become the current life science research One of the hot spots. The acquisition and processing of physiological and medical signals is an important technology in biomedical engineering, which provides a necessary benchmark for the research of sports physiology and medicine. This article aims to provide some ideas and directions for the research on collecting physiological signal data of athletes under the cloud computing environment and the application of Internet of Things technology.and mainly introduces the design of the intelligent acquisition system of physiological signal data of athletes under cloud computing. This paper proposes an intelligent acquisition method for athletes’ physiological signal data under cloud computing, including the design of power frequency filter and the energy model of the TDMA protocol system, which is used to conduct research experiments on the design of an athlete’s physiological signal data intelligent acquisition system under cloud computing. The experimental results of this article show that the average collection accuracy rate of the system is 97.01%, the test of the intelligent acquisition system shows that the stability of the system is very high, and the accuracy rate is high, which can better collect the physiological signal data of athletes.

生理信号研究的应用背景侧重于生命科学、临床诊断和监测应用领域的教育和研究，是生物医学工程领域的重要内容。智能生理信号采集系统的开发和使用也成为当前生命科学研究的热点之一。生理和医学信号的采集和处理是生物医学工程中的一项重要技术，为运动生理学和医学研究提供了必要的基准。本文旨在为云计算环境下运动员生理信号数据采集研究及物联网技术应用提供一些思路和方向。并主要介绍了云计算下运动员生理信号数据智能采集系统的设计。本文提出了一种云计算下运动员生理信号数据的智能采集方法，包括工频滤波器的设计和TDMA协议系统的能量模型，用于对运动员生理信号数据的设计进行研究实验。云计算下的智能采集系统。本文实验结果表明，该系统的平均采集准确率为97.01%，智能采集系统的测试表明，该系统的稳定性非常高，准确率高，可以更好地采集运动员的生理信号数据。