<abstract> <p>Due to the complexity of three-dimensional (3D) human pose, it is difficult for ordinary sensors to capture subtle changes in pose, resulting in a decrease in the accuracy of 3D human pose detection. A novel 3D human motion pose detection method is designed by combining Nano sensors and multi-agent deep reinforcement learning technology. First, Nano sensors are placed in key parts of the human to collect human electromyogram (EMG) signals. Second, after de-noising the EMG signal by blind source separation technology, the time-domain and frequency-domain features of the surface EMG signal are extracted. Finally, in the multi-agent environment, the deep reinforcement learning network is introduced to build the multi-agent deep reinforcement learning pose detection model, and the 3D local pose of the human is output according to the features of the EMG signal. The fusion and pose calculation of the multi-sensor pose detection results are performed to obtain the 3D human pose detection results. The results show that the proposed method has high accuracy for detecting various human poses, and the accuracy, precision, recall and specificity of 3D human pose detection results are 0.97, 0.98, 0.95 and 0.98, respectively. Compared with other methods, the detection results in this paper are more accurate, and can be widely used in medicine, film, sports and other fields.</p> </abstract>

The algorithms of wearable image processing technology equipment have certain versatility and can be widely used in popular fields such as medical treatment, factories, drone development, human-computer interaction, virtual reality, and physical education. In order to deeply study the monitoring effect of smart wearable products based on the image processing technology on basketball training postures, this article uses the product manual comparison method, data collection method, and equipment development method to collect samples and analyze and develop intelligent monitoring equipment, streamlined algorithm. And it integrated and developed a wearable product that can monitor athletes’ training posture in real time during basketball training. After the product was researched, the training program of the product was used for low-handed dribbling. The first training lasted for 3 minutes and 10 seconds, and the second training lasted for 2 minutes and 45 seconds. The prototype and manual dribbles were studied in these two cases. The results showed that the prototype reminded the participants 31 times, while the coach only reminded them 13 times due to the large number of people. By comparing the satisfaction scores of the fitness software and the products developed in this article, the score ranges from 1 to 5 points, which is very consistent with the score of 5, and it is very inconsistent with the score of 1. Through the trial of this scene, positive information was obtained. The evaluation of the prototype is generally above that of the fitness software. The number of people eager to use the prototype again is 10 times more than that of the fitness software. These data are from the first combination chart and the third combination chart. The corresponding explanations and experimental methods will be introduced in the description of these two combination charts later. The prototype can widely cater to the public’s sport preferences. It is basically realized that starting from the image processing technology, a smart monitoring wearable product with high evaluation and good effect has been designed.

Aiming at the problem of the fairness of the judgment results in the traditional basketball referee training and evaluation process affected by external factors, an intelligent system for training and assessment of basketball referees in sports events based on intelligent sensors is proposed. We collect the judged poses of basketball referees by wearing intelligent sensor devices, store the collected information in the database using the converter, and analyze the pose data with the quaternion pose solution method based on complementary filters. According to the comparator, the analysis result is compared with the standard judgment information, and the action is judged whether the action conforms to the basketball judgment rules of the sports event. The judge’s action pose score is evaluated according to the judgment result, and the training assessment result is outputted. The results show that the system can clearly simulate the acceleration and pose angle data of the referee’s complex actions, the recognition rate of various basketball penalty poses is high, and the error of the pitch, yaw, and roll pose calculations is small. The response time of this system is 4 ms, when the number of requests sent by the client is 200 which is unanimously approved by the referees.

Wrist joint plays an indispensable role in our daily life. The injury of wrist joint has a great influence on the fine movement of the hand and upper limb. For example, you cannot do joint movements, you cannot carry things, and life is very inconvenient. It is necessary to distinguish the types of wrist disorders and take effective rehabilitation methods in time. Wrist joint has a great impact on people’s life and work, and the rehabilitation of wrist joint has become a research hotspot in rehabilitation medicine and medical engineering. Carpal tunnel syndrome is the most common peripheral nerve entrapment disease in clinical practice, with a very high incidence. According to data, the incidence of carpal tunnel syndrome in the general population abroad is 1%-5%, while that in special populations is as high as 14.5% above. In order to solve the problem of rehabilitation of wrist joint, using electrospinning technology, the polymer solution is prepared into nanofiber materials with strong adsorption and good filterability under the action of high-voltage electric field. And using some small-sized nanofibers that are similar to organs in shape and structure, as well as their excellent degradability and biocompatibility, this material is used in the research of wrist joint movement rehabilitation. In this paper, sports rehabilitation training is carried out on the wrist joint of basketball players, and the nanofiber material is effectively combined with sports rehabilitation training. By comparing the rehabilitation of athletes who did not use nanofiber materials, the role of nanofiber materials in sports rehabilitation was studied. This article analyzes the three parts of the radial joint, the wrist joint, and the ulnar joint before and after the sports rehabilitation training for basketball players with functional impairments and compares the sports rehabilitation of the basketball players without nanofiber materials. This article analyzes the three parts of the radial joint, the wrist joint, and the ulnar joint before and after the sports rehabilitation training for basketball players with functional impairments and compares the sports rehabilitation of the basketball players without nanofiber materials.