{"title":"基于腕带惯性运动传感器的电吉他基本拾取分析系统","authors":"Soichiro Matsushita;Ayaka Takamoto","doi":"10.1109/JSEN.2025.3526983","DOIUrl":null,"url":null,"abstract":"A wrist-worn inertial motion-sensing device with a high sampling frequency was applied to evaluate fundamental electric guitar picking. A combinatorial analysis using wrist-twisting angular jerk and time-differential vertical jerk signals detected on the player’s dominant wrist achieved accurate picking timing estimation. The developed signal-processing algorithm eliminated motion artifacts such as vibration from the guitar strings, especially in the case of the palm mute technique. The timing differences between the motion-based method using a sampling frequency of 1024 Hz and a sound-based onset timing analysis method as ground truth were less than 10 ms. In addition, it was found that the amplitude of sound and the time duration of picking for each note can be determined in the form of motion parameters without using sound signals. A population test in a 14-week-long guitar lesson class with 12 beginners showed convincing results that reflected the difficulties of the chord strumming and the single-note picking techniques.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"8849-8856"},"PeriodicalIF":4.3000,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fundamental Picking Analysis System for Electric Guitar Using Wrist-Worn Inertial Motion Sensors\",\"authors\":\"Soichiro Matsushita;Ayaka Takamoto\",\"doi\":\"10.1109/JSEN.2025.3526983\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A wrist-worn inertial motion-sensing device with a high sampling frequency was applied to evaluate fundamental electric guitar picking. A combinatorial analysis using wrist-twisting angular jerk and time-differential vertical jerk signals detected on the player’s dominant wrist achieved accurate picking timing estimation. The developed signal-processing algorithm eliminated motion artifacts such as vibration from the guitar strings, especially in the case of the palm mute technique. The timing differences between the motion-based method using a sampling frequency of 1024 Hz and a sound-based onset timing analysis method as ground truth were less than 10 ms. In addition, it was found that the amplitude of sound and the time duration of picking for each note can be determined in the form of motion parameters without using sound signals. A population test in a 14-week-long guitar lesson class with 12 beginners showed convincing results that reflected the difficulties of the chord strumming and the single-note picking techniques.\",\"PeriodicalId\":447,\"journal\":{\"name\":\"IEEE Sensors Journal\",\"volume\":\"25 5\",\"pages\":\"8849-8856\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-01-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Journal\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10841957/\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10841957/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Fundamental Picking Analysis System for Electric Guitar Using Wrist-Worn Inertial Motion Sensors
A wrist-worn inertial motion-sensing device with a high sampling frequency was applied to evaluate fundamental electric guitar picking. A combinatorial analysis using wrist-twisting angular jerk and time-differential vertical jerk signals detected on the player’s dominant wrist achieved accurate picking timing estimation. The developed signal-processing algorithm eliminated motion artifacts such as vibration from the guitar strings, especially in the case of the palm mute technique. The timing differences between the motion-based method using a sampling frequency of 1024 Hz and a sound-based onset timing analysis method as ground truth were less than 10 ms. In addition, it was found that the amplitude of sound and the time duration of picking for each note can be determined in the form of motion parameters without using sound signals. A population test in a 14-week-long guitar lesson class with 12 beginners showed convincing results that reflected the difficulties of the chord strumming and the single-note picking techniques.
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