Correction to: Scientific Reports 10.1038/s41598-024-74526-x, published online 03 October 2024
The original version of this Article contained errors. After publication, the Authors noticed that some of their statements could be interpreted as if the development of the acceleration sensor was part of this work. However, the sensor was developed and published previously by some of the same Authors in [1] and [2] (references 21 and 22 in the original published Article).
To attribute this, the Author byline:
Jingyu Quan, Hirotaka Uchitomi, Ryo Shigeyama, Chenguang Gao, Taiki Ogata, Akira Inaba, Satoshi Orimo & Yoshihiro Miyake
now reads:
Jingyu Quan, Hirotaka Uchitomi, Ryo Shigeyama, Chenguang Gao, Taiki Ogata, Akira Inaba, Satoshi Orimo, Hiroyuki Ito, Katsuyuki Machida, Masato Sone & Yoshihiro Miyake
In addition, the Title of the Article:
High-sensitivity acceleration sensor detecting micro-mechanomyogram and deep learning approach for parkinson’s disease classification.
now reads:
Application of high-sensitivity acceleration sensor detecting micro-mechanomyogram and deep learning for Parkinson’s disease classification.
In the first paragraph of the ‘Introduction’ section, the sentence:
Specifically, we developed an acceleration sensor with great sensitivity to vibration than commercial sensors.
now reads:
Specifically, we developed an acceleration sensor with great sensitivity to vibration than commercial sensors as previously reported [21], [22].
In the Methods section, under the subheading ‘Method for measurement of micro-mechanomyogram and motor symptoms’ in the section ‘Measurement system’, in the following sentence reference 22 was omitted:
Based on the developed high-sensitivity acceleration sensor, we implemented a sensor module for measuring MMG [21].
It now reads:
Based on the developed high-sensitivity acceleration sensor, we implemented a sensor module for measuring MMG [21] [22].
The figure legend of Fig. 1:
Fig. 1 High-sensitivity acceleration sensor and experimental setup. (a) High-sensitivity acceleration sensor and sensor module [21]. (b) Power spectral density of noise floor in the high-sensitivity acceleration sensor. (c) Experimental scene including sensor box housing sensor module, microcontroller, and PC. Note that this figure is included in the published paper with written informed consent from the participant in the figure. (d) Sensor module position on flexor pollicis brevis muscle. (e) Measurement conditions consisting of Rest and Pinch conditions. CDC, capacitance digital converter; I2C, inter-integrated circuit; PC, personal computer; USB, Universal Serial Bus.
now reads:
Fig. 1 High-sensitivity acceleration sensor and experimental setup. (a) High-sensitivity acceleration sensor and sensor module [21] [22]. (b) Power spectral density of noise floor in the high-sensitivity acceleration sensor [21] [22]. (c) Experimental scene including sensor box housing sensor module, microcontroller, and PC. Note that this figure is included in the published paper with written informed consent from the participant in the figure. (d) Sensor module position on flexor pollicis brevis muscle. (e) Measurement conditions consisting of Rest and Pinch conditions. CDC, capacitance digital converter; I2C, inter-integrated circuit; PC, personal computer; USB, Universal Serial Bus.
Furthermore, due to the addition of Authors, in the Author contributions section:
JQ, HU, RS, CG, TO, and YM contributed to the study conception and design, developed and implemented the experimental systems, conducted the experiment, and discussed and interpreted the results. JQ and HU drafted the manuscript. JQ, HU, RS, CG, TO, and YM reviewed the manuscript.
now reads:
JQ, HU, RS, CG, TO, and YM contributed to the study conception and design. RS, TO, HI, KM, MS, and YM developed and implemented the experimental systems. RS, TO and SO conducted the experiment. JQ, HU, RS, CG, TO, and YM performed feature analysis and statistical analysis. JQ, HU, and YM built a deep learning model and evaluated its performance. All authors discussed and interpreted the results. JQ and HU drafted the manuscript. All authors reviewed the manuscript.
The original Article has been corrected.
[1] Onishi, A. et al. Suppressed drift and low-noise sensor module with a single-axis gold proof-mass MEMS accelerometer for micro muscle sound measurement. Jpn J. Appl. Phys.61, SD1028. 10.35848/1347-4065/ac5b25) (2022).
[2] Koga, T. et al. High-sensitivity inertial sensor module to measure hidden micro muscular sounds. Proceedings of the of the 2019 IEEE Biomed. Circuits and Systems Conference (BioCAS), Nara, Japan, Oct 17–19, 2019 (10.1109/BIOCAS.2019.8919151).