Inertial sensor for objective evaluation of swimmer performance

Daukantas, Saulius; Marozas, Vaidotas; Lukoševičius, Arūnas

doi:10.1109/bec.2008.4657545

Cited by 24 publications

(23 citation statements)

References 3 publications

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“…In the gym, sensor data from balance board training [14,15] has been used to provide feedback on the performance quality. Furthermore, body-worn inertial sensors have been used for the assessment of (professional) athletes in sports such as snow-boarding [16], swimming [17] and running [18]. Beyond applications in sports, similar systems have been employed to assess professional skills, e.g.…”

Section: Automatic Assessment Of Physical Activitymentioning

confidence: 99%

The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices

Kranz

Möller

Hammerla

et al. 2013

Pervasive and Mobile Computing

168

105

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a b s t r a c tWe report on our extended research on GymSkill, a smartphone system for comprehensive physical exercising support, from sensor data logging, activity recognition to on-top skill assessment, using the phone's built-in sensors. In two iterations, we used principal component breakdown analysis (PCBA) and criteria-based scores for individualized and personalized automated feedback on the phone, with the goal to track training quality and success and give feedback to the user, as well as to engage and motivate regular exercising. Qualitative feedback on the system was collected in a user study, and the system showed good evaluation results in an evaluation against manual expert assessments of videorecorded trainings.

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Section: Automatic Assessment Of Physical Activitymentioning

confidence: 99%

The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices

Kranz

Möller

Hammerla

et al. 2013

Pervasive and Mobile Computing

168

105

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“…First the orientation of the sensors was calculated with a sensor fusion algorithm [17] using the direction cosine 5 . The algorithm calculates a robust orientation of the device based on the data from the magnetometer, the gyroscope, and the accelerometer.…”

Section: Resultsmentioning

confidence: 99%

“…Swimming as a sport got also some attention in research. Daukantas et al [5] made a first step towards measuring swimming performance of butterfly strokes with inertial sensors attached to the swimmers' spine. Their work reveals several problems when trying to assess the moving speed from acceleration data.…”

Section: Activity Trackingmentioning

confidence: 99%

ClimbSense

Kosmalla

Daiber

Krüger

2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

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Today, sports and activity trackers are ubiquitous. Especially runners and cyclists have a variety of possibilities to record and analyze their workouts. In contrast, climbing did not find much attention in consumer electronics and human-computer interaction. If quantified data similar to cycling or running data were available for climbing, several applications would be possible, ranging from simple training diaries to virtual coaches or usage analytics for gym operators.This paper introduces a system that automatically recognizes climbed routes using wrist-worn inertia measurement units (IMUs). This is achieved by extracting features of a recorded ascent and use them as training data for the recognition system. To verify the recognition system, cross-validation methods were applied to a set of ascent recordings that were assessed during a user study with eight climbers in a local climbing gym. The evaluation resulted in a high recognition rate, thus proving that our approach is possible and operational.

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“…First, there is swimming style (freestyle, backstroke, breaststroke and butterfly). Second, there is the turn type, and third, there is swimming intensity (speed or resistance) [14,32,33,34,35,36,37,38,39,40,41,42,43]. …”

Section: Sportsmentioning

confidence: 99%

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

Mendes

Vieira

Pires

et al. 2016

Sensors

100

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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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Inertial sensor for objective evaluation of swimmer performance

Cited by 24 publications

References 3 publications

The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices

The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices

ClimbSense

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

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