## 5 Conclusions and Future Work  
By the progress of 5G and wireless communication techniques, the interdisciplinary research integrated with wireless domain has become an important research issue recently. By the advancement of medical technology, the number of people with rehabilitation was increased. Hence, how to integrate the wireless communication with medical techniques was the main object of this paper. Among all kinds of rehabilitation, the elbow joint rehabilitation occurred commonly and most of elbow joint rehabilitation could by executed at home after discussion with an Orthopedist. To reduce the time and money for patients with elbow joint rehabilitation, and to reduce the resource and manpower for a hospital, a wearable device for residential elbow joint rehabilitation detection with voice prompts and a tracking feedback APP, WDREJARPP, was proposed in this paper. WDREJARPP included the wearable device for residential elbow joint rehabilitation detection with voice prompts (WDREJHVP) and a tracking feedback APP (TFAPP). The WDREJHVP aimed to capture the action of rehabilitation and examine whether the action was correct or incorrect. Then, WDREJHVP automatically transmitted the detected data of rehabilitation to TFAPP via Bluetooth. While TFAPP received the data of rehabilitation from WDREJHVP, TFAPP automatically uploaded the data to the cloud database in real time. Once WDREJHVP examined the incorrect action of rehabilitation, the simulated patients could receive the voice prompts from TFAPP to calibrate the action of rehabilitation to achieve the required number of rehabilitation. In the experimental results, the rate of correct elbow joint rehabilitation detection (\(R\)) could be up to 90% in a general situation. Another contribution of this paper is to provide the data querying, remote setting, feedback messages, and voice prompts in TFAPP that we designed for the simulated patients and medical staff. Different from other APPs, the main contribution of TFAPP was that the program of elbow joint rehabilitation was set and judged by medical staff, since the simulated patients had no medical professional ability. The simulated patients cannot set or judge the program of elbow joint rehabilitation. In this condition, it could have the better efficiency of rehabilitation than other APPs. In the experimental results, it showed that each function was working normally and could be used for the simulated patients and medical staff in any time and any place via the internet. In conclusion, WDREJARPP provided a wearable device and APP for the residential elbow joint rehabilitation detection in real time. In addition, WDREJARPP reduced the time, money, resources, and manpower for the simulated patients and hospital. However, some issues were found in the experimental results. The first issue was that the rate of correct elbow joint rehabilitation detection may be decreased and below 90% while the frequency of elbow joint rehabilitation was too high or too slow. For this issue, WDVP will be improved to judge the capturing time of WDVP by the medical staff based on the simulated patient's status of rehabilitation. Another issue was that TFAPP may not be suitable for iOS. Hence, we will design TFAPP through Node.js replaced by App Inventor 2 to be used in both of Android and iOS mobile operation systems in the future. Since our research was the pilot study and the patients were simulated by our team users not real patients, we will send the IRB our research in the future. **Author Contributions:** [PERSON] developed the research contents based on the analysis and experiments, drafted the manuscript, and directed the research process. [PERSON] was responsible for the experiment results. [PERSON] supervised the overall work. All authors have read and agreed to the published version of the manuscript. **Funding:** This paper was supported by the Ministry of Science and Technology (MOST) of Taiwan to National Taitung University under 109-2813-C-143-006-E.  
**Informed Consent Statement:** Not applicable.