Smart Kote Glove for Assessment of Scoring Parameters of Dan and Kyu Grade Kendokas

Jeong, Kwangyul; Tan, Adin Ming; Fuss, Franz Konstantin

doi:10.3390/proceedings2060225

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…(9,10) In kendo, there are also some studies conducted to evaluate the proficiency level of strike activities using acceleration and pressure sensors attached to shinai (bamboo swords) and armor. (11,12) However, to the best of our knowledge, no study has been conducted to detect and recognize strike activities to monitor kendo players using IMUs. In this paper, we focus on kendo, which is a traditional martial art in Japan, and propose a method for detecting and recognizing strike activities using IMUs towards realizing a kendo skill improvement support system.…”

Section: Introductionmentioning

confidence: 99%

Strike Activity Detection and Recognition Using Inertial Measurement Unit towards Kendo Skill Improvement Support System

Torigoe

Nakamura

Fujimoto

et al. 2020

Sensors and Materials

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In the field of sports, there are increasing opportunities to use inertial measurement units (IMUs) to enhance the training process and improve the performance of athletes. We focus on kendo, a traditional martial art using shinai (bamboo swords) in Japan, and propose methods for detecting and recognizing strike activities using IMUs towards realizing a kendo skill improvement support system. We used a sensor data set of strike activities obtained from 14 participants (seven kendo-experienced and seven inexperienced persons). We attached four IMUs to the participants' right wrist, waist, and shinai (tsuba and saki-gawa). First, to detect the strike activity, we calculated the dynamic time warping (DTW) distance between the training data and the time series data, and detected the strike activity sections. The proposed method detected strike activities with a high accuracy of 95.0%. Next, to recognize the strike activity, we recognized five types (Center-Men, Right-Men, Left-Men, Dō, and Kote). In the person-dependent (PD) case, we achieved an accuracy of 89.5% using data of the right wrist. In the person-independent (PI) case, we achieved an accuracy of 54.9% using IMUs attached to the three positions. These results clarified the points to be improved in the proposed method to realize the support system.

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Section: Introductionmentioning

confidence: 99%

Strike Activity Detection and Recognition Using Inertial Measurement Unit towards Kendo Skill Improvement Support System

Torigoe

Nakamura

Fujimoto

et al. 2020

Sensors and Materials

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Pegasos: a framework for the creation of direct mobile coaching feedback systems

Dobiasch,

Oppl,

Stöckl

et al. 2023

J Multimodal User Interfaces

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Feedback is essential for athletes in order to improve their sport performance. Feedback systems try to provide athletes and coaches not only with visualisations of acquired data, but moreover, with insights into—possibly—invisible aspects of their performance. With the widespread adoption of smartphones and the increase in their capabilities, their use as a device for applications of feedback systems is becoming increasingly popular. However, developing mobile feedback systems requires a high level of expertise from researchers and practitioners. The Direct Mobile Coaching model is a design-paradigm for mobile feedback systems. In order to reduce programming efforts, PEGASOS, a framework for creating feedback systems implementing the so-called Direct Mobile Coaching model, is introduced. The paper compares this framework with state-of-the-art research with regard to their ability of providing different variants feedback and offering multimodality to users.

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Direct Mobile Coaching as a Paradigm for the Creation of Mobile Feedback Systems

et al. 2022

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In sports feedback systems, digital systems perform tasks such as capturing, analysing and representing data. These systems not only aim to provide athletes and coaches with insights into performances but also help athletes learn new tasks and control movements, for example, to prevent injuries. However, designing mobile feedback systems requires a high level of expertise from researchers and practitioners in many areas. As a solution to this problem, we present Direct Mobile Coaching (DMC) as a design paradigm and model for mobile feedback systems. Besides components for feedback provisioning, the model consists of components for data recording, storage and management. For the evaluation of the model, its features are compared against state-of-the-art frameworks. Furthermore, the capabilities are benchmarked using a review of the literature. We conclude that DMC is capable of modelling all 39 identified systems while other identified frameworks (MobileCoach, Garmin Connect IQ SDK, RADAR) could (at best) only model parts of them. The presented design paradigm/model is applicable for a wide range of mobile feedback systems and equips researchers and practitioners with a valuable tool.

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Smart Kote Glove for Assessment of Scoring Parameters of Dan and Kyu Grade Kendokas

Cited by 3 publications

References 6 publications

Strike Activity Detection and Recognition Using Inertial Measurement Unit towards Kendo Skill Improvement Support System

Strike Activity Detection and Recognition Using Inertial Measurement Unit towards Kendo Skill Improvement Support System

Pegasos: a framework for the creation of direct mobile coaching feedback systems

Direct Mobile Coaching as a Paradigm for the Creation of Mobile Feedback Systems

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