PPG2EMG: Estimating Upper-Arm Muscle Activities and EMG from Wrist PPG Values
The electromyogram (EMG) is a waveform representation of the action potential generated by muscle cells using electrodes. EMG acquired using surface electrodes is called surface EMG (sEMG), and it is the acquisition of muscle action potentials transmitted by volume conduction from the skin. Surface...
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MDPI AG
2023-02-01
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| Online Access: | https://www.mdpi.com/1424-8220/23/4/1782 |
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| author | Masahiro Okamoto Kazuya Murao |
| author_facet | Masahiro Okamoto Kazuya Murao |
| author_sort | Masahiro Okamoto |
| collection | DOAJ |
| description | The electromyogram (EMG) is a waveform representation of the action potential generated by muscle cells using electrodes. EMG acquired using surface electrodes is called surface EMG (sEMG), and it is the acquisition of muscle action potentials transmitted by volume conduction from the skin. Surface electrodes require disposable conductive gel or adhesive tape to be attached to the skin, which is costly to run, and the tape is hard on the skin when it is removed. Muscle activity can be evaluated by acquiring muscle potentials and analyzing quantitative, temporal, and frequency factors. It is also possible to evaluate muscle fatigue because the frequency of the EMG becomes lower as the muscle becomes fatigued. Research on human activity recognition from EMG signals has been actively conducted and applied to systems that support arm and hand functions. This paper proposes a method for recognizing the muscle activity state of the arm using pulse wave data (PPG: Photoplethysmography) and a method for estimating EMG using pulse wave data. This paper assumes that the PPG sensor is worn on the user’s wrist to measure the heart rate. The user also attaches an elastic band to the upper arm, and when the user exerts a force on the arm, the muscles of the upper arm contract. The arteries are then constricted, and the pulse wave measured at the wrist becomes weak. From the change in the pulse wave, the muscle activity of the arm can be recognized and the number of action potentials of the muscle can be estimated. From the evaluation experiment with five subjects, three types of muscle activity were recognized with 80+%, and EMG was estimated with approximately 20% error rate. |
| first_indexed | 2024-03-11T08:12:08Z |
| format | Article |
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| language | English |
| last_indexed | 2024-03-11T08:12:08Z |
| publishDate | 2023-02-01 |
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| spelling | doaj.art-ba59617105a84eb296167ee5566db5512023-11-16T23:06:07ZengMDPI AGSensors1424-82202023-02-01234178210.3390/s23041782PPG2EMG: Estimating Upper-Arm Muscle Activities and EMG from Wrist PPG ValuesMasahiro Okamoto0Kazuya Murao1Graduate School of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga 525-8577, JapanGraduate School of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga 525-8577, JapanThe electromyogram (EMG) is a waveform representation of the action potential generated by muscle cells using electrodes. EMG acquired using surface electrodes is called surface EMG (sEMG), and it is the acquisition of muscle action potentials transmitted by volume conduction from the skin. Surface electrodes require disposable conductive gel or adhesive tape to be attached to the skin, which is costly to run, and the tape is hard on the skin when it is removed. Muscle activity can be evaluated by acquiring muscle potentials and analyzing quantitative, temporal, and frequency factors. It is also possible to evaluate muscle fatigue because the frequency of the EMG becomes lower as the muscle becomes fatigued. Research on human activity recognition from EMG signals has been actively conducted and applied to systems that support arm and hand functions. This paper proposes a method for recognizing the muscle activity state of the arm using pulse wave data (PPG: Photoplethysmography) and a method for estimating EMG using pulse wave data. This paper assumes that the PPG sensor is worn on the user’s wrist to measure the heart rate. The user also attaches an elastic band to the upper arm, and when the user exerts a force on the arm, the muscles of the upper arm contract. The arteries are then constricted, and the pulse wave measured at the wrist becomes weak. From the change in the pulse wave, the muscle activity of the arm can be recognized and the number of action potentials of the muscle can be estimated. From the evaluation experiment with five subjects, three types of muscle activity were recognized with 80+%, and EMG was estimated with approximately 20% error rate.https://www.mdpi.com/1424-8220/23/4/1782wearable computingsensingpulse waveelectromyogramPPGEMG |
| spellingShingle | Masahiro Okamoto Kazuya Murao PPG2EMG: Estimating Upper-Arm Muscle Activities and EMG from Wrist PPG Values Sensors wearable computing sensing pulse wave electromyogram PPG EMG |
| title | PPG2EMG: Estimating Upper-Arm Muscle Activities and EMG from Wrist PPG Values |
| title_full | PPG2EMG: Estimating Upper-Arm Muscle Activities and EMG from Wrist PPG Values |
| title_fullStr | PPG2EMG: Estimating Upper-Arm Muscle Activities and EMG from Wrist PPG Values |
| title_full_unstemmed | PPG2EMG: Estimating Upper-Arm Muscle Activities and EMG from Wrist PPG Values |
| title_short | PPG2EMG: Estimating Upper-Arm Muscle Activities and EMG from Wrist PPG Values |
| title_sort | ppg2emg estimating upper arm muscle activities and emg from wrist ppg values |
| topic | wearable computing sensing pulse wave electromyogram PPG EMG |
| url | https://www.mdpi.com/1424-8220/23/4/1782 |
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