# Wearable Sensors for Vital Signs Measurement: A Survey
## 3 Intelligent Prospect of Wearable Medical Sensors
### Intelligent Prospective Applications of Wearable Medical Sensors
#### 3.2.3 Prospects of Intelligence-Assisted Rehabilitation of Wearable Medical Sensors
They found that the gyroscope and sEMG integrated in wearable devices could simultaneously sense the motion and action potential of antagonistic leg muscles [79]. A review of the research of the above-mentioned scholars found that due to the development of sensing technology, cheaper integrated circuits and connection technology, wearable devices and sensing devices used to monitor physical activity, whether for health, sports monitoring or medical rehabilitation, have been rapidly expanded. However, the construction of the actual medical sensor-assisted rehabilitation systems involves robotics, ergonomics, control theory, sensor technology, information-processing technology, and other disciplines, which require the integration of a variety of high-tech technologies [80; 81]. Thus, the driving system, perception system, control system, man-machine matching system, man-machine interaction system and battery management system of any medical-sensor-assisted rehabilitation system are all extremely critical. Therefore, while some breakthroughs and progress have been made for medical sensor-assisted rehabilitation systems, continuous improvement should include the modularization of the exoskeleton structure, the intelligitization of the control system, and the improvement of the performance evaluation of rehabilitation training effects. The theoretical research of modularization can be summarized as modular design of complex products, modular design of complex systems, and modular construction of industrial organization. The exoskeleton robot is divided into modules according to certain rules to make each module function independent and targeted, reduce the complexity of the exoskeleton robot, make breakthroughs in scientific research easier, and ultimately better meet the actual needs of different users [82]. In the intelligitization of control systems, the advent of the 5G era is promoting the in-depth development of artificial intelligence technology. The exoskeleton robot control system should keep pace with the times, so that the robot can learn independently, realize intelligent control, make operation simple and easy, enhance the user experience, and realize more comfortable and humanized rehabilitation training [83]. The improvement of the ability to evaluate the effects of rehabilitation training enables exoskeleton robots to successfully complete human-machine coordinated motion [84]. In the current rehabilitation training process, its power-assisted ability, power-assisted effect, bone stability, metabolic value, wearer fatigue, etc. cannot be monitored and presented. In the follow-up, real-time evaluation of the rehabilitation effect will be achieved by presenting the medical effect of each rehabilitation training. This will enable medical staff to formulate corresponding strategies in time, which will have a great effect on rehabilitation training. 2.4 Prospect of Intelligent Prediction Based on the Combination of Wearable Medical Sensors and Intelligent Algorithms  
In recent years, the development of artificial intelligence and the research into artificial intelligence in the medical field have gradually begun, making people aware of the good prospects for the integration of artificial intelligence and medical care. Among them, the combination of the popular deep-learning field and sensor data-acquisition technology has shown relatively great application potential in disease prediction and drug response prediction [85]. Many researchers in related fields have conducted research into this combination. [PERSON] et al. (2017) described the architecture of a typical system based on wearable medical sensors and discussed various research directions relating to wearable medical sensors, and how previous studies tried to solve the limitations of components used in wearable medical sensors system to meet the ideal design goal of an intelligent algorithm applied to wearable medical sensors [86]. [PERSON] et al.