基于腕带惯性运动传感器的电吉他基本拾取分析系统

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Soichiro Matsushita;Ayaka Takamoto
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引用次数: 0

摘要

采用一种高采样频率的腕式惯性运动传感装置对电吉他的基本拾取进行了评价。组合分析手腕扭角抽搐和时间差垂直抽搐信号检测到的球员的主手腕实现准确的采摘时间估计。所开发的信号处理算法消除了吉他弦的振动等运动伪影,特别是在手掌静音技术的情况下。基于运动的采样频率为1024 Hz的方法与基于声音的起始时间分析方法作为地真值的时间差异小于10 ms。此外,发现声音的振幅和每个音符的拾取时间持续时间可以在不使用声音信号的情况下以运动参数的形式确定。对12名初学者进行的为期14周的吉他课的总体测试显示,令人信服的结果反映了和弦弹奏和单音拾取技术的困难。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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