This paper presents a miniature wearable device and a system for detecting and recording the movement and biometric information of a user during sport activities. The wearable device is designed to be worn on a wrist and can monitor skin temperature and pulse rate. Furthermore, it can monitor arm movement and detect gestures using inertial measurement unit. The device can be used for various professional and amateur sport applications and for health monitoring. Because of its small size and minimum weight, it is especially appropriate for swing-based sports like tennis or golf, where any additional weight on the arms would most likely disturb the player and have some influence on the player's performance. Basic signal processing is performed directly on the wearable device but for more complex signal analysis, the data can be uploaded via the Internet to a cloud service, where it can be processed by a dedicated application. The device is powered by a lightweight miniature LiPo battery and has about 6 h of autonomy at maximum performance.

This paper presents work related to tennis stroke detection and classification. For arm movement acquisition a miniature wearable IMU device, positioned on the player's forearm (right above the wrist) is proposed and presented. The device uses a MEMS-based accelerometer and gyroscope with 6-DOF. For reliable and accurate tennis stroke detection the information obtained from the accelerometer data is used, and for tennis stroke classification, information from gyroscope data is extracted and processed. The proposed system is able to detect and classify three most common tennis strokes: forehand, backhand, and serve. Because of limited memory and lack of processing power, the proposed algorithms for stroke detection and classification are quite simple, but are nonetheless capable of achieving high classification rate. Overall 98.1% tennis stroke classification accuracy was achieved.

This paper presents the work related to the identification of PRV (pulse rate variability) and SpO2 (blood oxidation content) using miniature wearable wrist device. The extension of currently widely used PPT (photo plethysmography) measuring technique is proposed. Most PPT devices only measure PR (pulse rate), but with minimum adaptations to the sensor, a wider range of parameters can be measured. Two of such parameters are PRV and SpO2. This set of parameters gives a better insight into ones physical and mental state than only PR parameter. In order to develop a device that does not obstruct the user in any way, we propose a miniature non-invasive wearable device, and algorithms that do not need any significant processing power in order to identify the biometric parameters. The device is a lightweight battery powered embedded system, that measures and analyses biometric data for later analysis in correlation with one's activity.

The purpose of this article is to present the use of a previously validated wearable sensor device, Armbeep, in a real-life application, to enhance a tennis player’s training by monitoring and analysis of the time, physiological, movement, and tennis-specific workload and recovery indicators, based on fused sensor data acquired by the wearable sensor—a miniature wearable sensor device, designed to be worn on a wrist, that can detect and record movement and biometric information, where the basic signal processing is performed directly on the device, while the more complex signal analysis is performed in the cloud. The inertial measurements and pulse-rate detection of the wearable device were validated previously, showing acceptability for monitoring workload and recovery during tennis practice and matches. This study is one of the first attempts to monitor the daily workload and recovery of tennis players under real conditions. Based on these data, we can instruct the coach and the player to adjust the daily workload. This optimizes the level of an athlete’s training load, increases the effectiveness of training, enables an individual approach, and reduces the possibility of overuse or injuries. This study is a practical example of the use of modern technology in the return of injured athletes to normal training and competition. This information will help tennis coaches and players to objectify their workloads during training and competitions, as this is usually only an intuitive assessment.

This paper presents research made on the topic of how consistent a tennis player is when hitting a stroke. The analysis is made preliminarily only for the most common tennis stroke, which is forehand. The analysis results can be very useful for the tennis coaches and other experts on the evaluation of a tennis player's current shape and performance stability. For swing movement acquisition a miniature wearable device is used. It is positioned on a player's forearm above the wrist and uses accelerometer and gyroscope to record acceleration and angular velocity in all three axes. A wearable device is a part of the system-in-a-cloud service where complex and more detailed game/performance analyses can be performed.