Sport Sense: A mobile sensor data collection, labeling and display application for sport centers

Can, Yekta Said; Donmez, Mehmet Yunus

doi:10.1109/siu.2015.7129901

Cited by 2 publications

(3 citation statements)

References 6 publications

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“…In addition to the already mentioned types of movements, other types of movements are essential in sports, such as swinging, which is characterized as a complete movement with a bat or racket to have contact with the ball at the optimum time and angle, which is used in sports such as tennis, golf, baseball, cricket, among others [74]. Based on this movement type, a system was developed to analyze the swinging applied to golf.…”

Section: Sportsmentioning

confidence: 99%

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Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

Mendes

Vieira

Pires

et al. 2016

Sensors

101

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The following work presents an overview of smart sensors and sensor fusion targeted at biomedical applications and sports areas. In this work, the integration of these areas is demonstrated, promoting a reflection about techniques and applications to collect, quantify and qualify some physical variables associated with the human body. These techniques are presented in various biomedical and sports applications, which cover areas related to diagnostics, rehabilitation, physical monitoring, and the development of performance in athletes, among others. Although some applications are described in only one of two fields of study (biomedicine and sports), it is very likely that the same application fits in both, with small peculiarities or adaptations. To illustrate the contemporaneity of applications, an analysis of specialized papers published in the last six years has been made. In this context, the main characteristic of this review is to present the largest quantity of relevant examples of sensor fusion and smart sensors focusing on their utilization and proposals, without deeply addressing one specific system or technique, to the detriment of the others.

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Section: Sportsmentioning

confidence: 99%

“…Inertial sensors are installed on the golf club, graphically raising the trajectory of the bat, as well as the position and time until contact with the ball. These analyses can lead to a breakthrough in golf teaching and also provide feedback to coach and athlete during training and competitions [74]. …”

Section: Sportsmentioning

confidence: 99%

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

Mendes

Vieira

Pires

et al. 2016

Sensors

101

View full text Add to dashboard Cite

show abstract

“…The use of new technologies in the health care and sport sectors is common [1]. There are some applications to track, for example, the course of running training and the technique of the athletes [2], [3]. Nevertheless, there are no such applications for the rehabilitation process.…”

Section: Introductionmentioning

confidence: 99%

Mobile quantification and therapy course tracking for gait rehabilitation

Alcaraz

Moghaddamnia

Peissig

2017

2017 22nd International Conference on Digital Signal Processing (DSP)

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Abstract-This paper presents a novel autonomous quality metric to quantify the rehabilitations progress of subjects with knee/hip operations. The presented method supports digital analysis of human gait patterns using smartphones. The algorithm related to the autonomous metric utilizes calibrated acceleration, gyroscope and magnetometer signals from seven Inertial Measurement Units (IMUs) attached on the lower body in order to classify and generate the grading system values. The developed Android application connects the seven IMUs via Bluetooth R and performs the data acquisition and processing in real-time. In total nine features per acceleration direction and lower body joint angle are calculated and extracted in real-time to achieve a fast feedback to the user. We compare the classification accuracy and quantification capabilities of Linear Discriminant Analysis (LDA), Principal Component Analysis (PCA) and Naive Bayes (NB) algorithms. The presented system is able to classify patients and control subjects with an accuracy of up to 100%. The outcomes can be saved on the device or transmitted to treating physicians for later control of the subjects improvements and the efficiency of physiotherapy treatments in motor rehabilitation. The proposed autonomous quality metric solution bears great potential to be used and deployed to support digital healthcare and therapy.

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Sport Sense: A mobile sensor data collection, labeling and display application for sport centers

Cited by 2 publications

References 6 publications

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

Mobile quantification and therapy course tracking for gait rehabilitation

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