Sport training using body sensor networks: a statistical approach to measure wrist rotation for golf swing

Ghasemzadeh, Hassan; Loseu, Vitali; Guenterberg, Eric; Jafari, Roozbeh

doi:10.4108/icst.bodynets2009.6035

Cited by 84 publications

(44 citation statements)

References 24 publications

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“…Combination of scavenging from body heat and respiration can be applied for monitoring of bedridden patients in hospital. Ambulation and sunlight can be used in military applications or in performance monitoring of outdoor sports like golf [49]. Ambulation and respiration can be used in case of athletes in training.…”

Section: Resource Management Classesmentioning

confidence: 99%

Research directions in energy-sustainable cyber–physical systems

Gupta

Mukherjee

Varsamopoulos

et al. 2011

Sustainable Computing: Informatics and Systems

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Section: Resource Management Classesmentioning

confidence: 99%

Research directions in energy-sustainable cyber–physical systems

Gupta

Mukherjee

Varsamopoulos

et al. 2011

Sustainable Computing: Informatics and Systems

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“…Venkatraman [9] analyzed a behavior of the animal is further extracted from the recorded acceleration data using neural network based pattern recognition algorithms. Ghasemzadeh [10] suggested a golf swing training system which incorporates wearable motion sensors to obtain inertial information and provide feedback on the quality of movements. Kevin [11] analyzed a theory, design, and evaluation of a miniature, wireless IMU (Initial Measurement Unit) that precisely measures the dynamics of a golf club used in putting.…”

Section: Introductionmentioning

confidence: 99%

A Three-Dimensional Motion Anlaysis of Horse Rider in Wireless Sensor Network Environments

Lee¹,

Kwak²

2014

ijacsa

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Abstract-This paper constructed a database of the national representative level of a professional horse-rider by wearing a motion-capture suit attached with 16 inertial sensors under an inertial sensor-based wireless network environment, then made a visual comparative analysis through a few methods (graphical and statistical) on the values of all motion features (elbow angle, knee angle, knee-elbow distance, backbone angle and hip position) classified depending on horse types (using two horses named Warm-blood and Thoroughbred) and footpace types (at a trot and a canter) and obtained by various methods of calculating Euclidean distance, the second cosine, maximum and minimum values, and made a comparative analysis depending on motion features of a horse-rider by using MVN studio software. In the study, the experimental results confirmed the validity of the proposed method of obtaining the motion feature database of a horse-rider in the wireless sensor network environment and making an analytical system.

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“…Recent projects, for example, have explored interactive golfing practice [21,22], and an early study [23] took an initial look at pitching analysis with wired accelerometers. Wireless, limb-mounted inertial nodes have also been used for exercise coaching [24] and mobile interactive entertainment driven by exercise [25].…”

Section: Introduction and Prior Workmentioning

confidence: 99%