# Current State of Robotics in Hand Rehabilitation after Stroke: A Systematic Review
## 3 Discussion  
The purpose of this paper is to (i) describe the existing research on hand rehabilitation robots, and (ii) describe the drive modes, control strategies, training modes, and hand state detection techniques of hand rehabilitation robots. The results show that in the existing research on commercial hand rehabilitation robots, it is important to focus not only on the mechanical structure part but most importantly on the system control and hand state monitoring aspects of hand rehabilitation robots in order to have the best hand rehabilitation results. In particular, commercial hand rehabilitation robots, cannot be separated from clinical trials. A successful technology needs to undergo extensive controlled trials before it can be brought to market quickly. For example, the research process of [PERSON] et al. [115] is a relatively complete one, from problem formulation to practice to validation.  
In the face of the severe situation of the aging population and a large number of stroke and hemiplegia patients, the research on hand functional rehabilitation robots will remain a relatively cutting-edge and popular field that can be explored in depth in recent years and in the coming decades. This paper reviews the development of hand rehabilitation robots, Drive mode, Control strategy, Training mode and Hand state detection technology. The problem is still a key and difficult issue in this field. Based on the summary of this paper, there are still many areas that need to be improved and enhanced in the future research of hand rehabilitation robots:  
1. Portability and comfort of hand rehabilitation robots. Although the hand rehabilitation robot has slowly changed from a rigid exoskeleton to a flexible wearable type, its weight has been greatly reduced, but its drive still uses motors or air pumps, which makes it difficult to carry for a long time and limits the scope of use of the hand rehabilitation robot. Moreover, the biological characteristics and kinematics of the human hand should be fully considered to avoid secondary injuries to the patient's hand.
2. Diversity and flexibility of human-robot interactions. Most of the same kind on the market cannot realize EEG signal control, and the product cannot be remotely and instantly monitored during operation, the patient cannot independently conduct rehabilitation training, and there is little effective feedback data available for extraction, and the training rhythm cannot be independently fine-tuned during the rehabilitation process.
3. Accuracy of hand state recognition. Improving the accuracy, stability, real-time and adaptiveness of hand detection and tracking is of great academic value and practical engineering significance for the control and detection of hand rehabilitation robots.
4. VR virtual task-oriented enhanced active rehabilitation training. Many hand rehabilitation robots have been combined with virtual reality technology. It is believed that as virtual reality (VR) technology continues to mature, future hand rehabilitation training will also be more interesting.  
In order to optimize the difficult trade-off between functionality and usability typical of hand functional rehabilitation robotics in everyday life, we have identified the above four future directions that are of great interest. As shown in Figure 14, we have compiled a conceptual figure of robotic solutions in post-stroke hand rehabilitation. Future work should include several of these directions of development as a way to address the specific needs and desires of the user to control the device.