For various types of non-invasive physiological parameter detection technologies based on photoplethysmography (PPG) signals, a non-invasive detection and management system for human physiological parameters is constructed, which consists of a hardware platform for wearable device and a software platform for data processing, analysis and model deployment. In this paper, based on the basic principle of PPG detection, combined with the information required for the non-invasive physiological parameter detection models, a set of wearable acquisition device is built for collecting multi-wavelength and multi-channel PPG signals from different positions of the user’s hand, and synchronously collecting body temperature and motion data, on the basis of which a data processing and analysis application is constructed based on the wearable device as the deployment platform for the non-invasive physiological parameter detection models, which realizes the processing and analysis of front-end data, and the users can realize their own health management needs by combining the data management and health assessment functions provided by the software. The realized wearable device can stably and effectively collect high-quality PPG signals, which provides a reliable data basis for the non-invasive physiological parameter detection models. Taking the non-invasive glucose detection model as an example, the root mean square error of the overall prediction result of the sample is 0.888 mmol/L, and the percentage of Clark’s error grid area A is 84.086%, the test results show good accuracy and followability, and the model is embedded in a software platform that can be used offline, which makes it easy for users to detect and manage their daily glucose levels. Users can easily collect and record PPG signal data through the platform, combined with diverse physiological parameters non-invasive detection models, to obtain a wealth of key parameters for human health assessment; in addition, the system also provides interfaces for parameter management to help users assess and manage their own health levels.