Radars have been under steady development to track, identify, image, and classify targets. Modern radar systems, with the help of embedded systems, have additional comprehensive signal processing capabilities. They can extract useful information from very noisy data, e.g. interference from the environment and unwanted echoes which is collectively known as clutter in radar terms. Concerning the healthcare industry, radar applications for detection of vital signs, i.e. breathing and heart rate, have been extensively developed during the last few decades. Modern radar systems are expected to be a large part of non-intrusive monitoring in the coming smart home industry, where vital signs need to be monitored in the currently aging population. The research presented here is to break new ground in the radar-based healthcare technology, enabling detection of cold-induced shivering to such level that the micro-shivering can be clearly identified. To simplify the radar software optimization, a commercially available radar kit with demo application and a muscle model system using a vibration generator is used. The model is quantified through precise measurements. A simulated human body vital sign plus shivering is applied. By optimizing the radar software, the shivering amplitude and frequency are measured.