A Wearable Dual-Channel Bioimpedance Spectrometer for Real-Time Muscle Contraction Detection

Kusche, Roman; Oltmann, Andra; Rostalski, Philipp

doi:10.1109/jsen.2024.3359284

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Other1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 46 publications

(44 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

A Real-Time Muscle Fatigue Detection System Based on Multifrequency EIM and sEMG for Effective NMES

Fernandez Schrunder,

Huang,

Rodriguez

et al. 2024

IEEE Sensors J.

View full text Add to dashboard Cite

A Real-Time Muscle Fatigue Detection System Based on Multifrequency EIM and sEMG for Effective NMES

Fernandez Schrunder,

Huang,

Rodriguez

et al. 2024

IEEE Sensors J.

View full text Add to dashboard Cite

Optical Muscle Contraction Detection via Frequency Multiplexed LEDs

Hauschild,

John,

Hellbrück

et al. 2024

2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

View full text Add to dashboard Cite

An Effective and Robust Parameter Estimation Method in a Self-Developed, Ultra-Low Frequency Impedance Spectroscopy Technique for Large Impedances

Kuljic,

Vizvari,

Gyorfi

et al. 2024

Electronics

View full text Add to dashboard Cite

Bioimpedance spectrum (BIS) measurements are highly appreciated in in vivo studies. This non-destructive method, supported by simple and efficient instrumentation, is widely used in clinical applications. The multi-frequency approach allows for the efficient extraction of the most information from the measured data. However, low-frequency implementations are still unexploited in the development of the technique. A self-developed BIS measurement technology is considered the pioneering approach for low (<5 kHz) and ultra-low (<100 Hz) frequency range studies. In this paper, the robustness of ultra-low frequency measurements in the prototypes is examined using specially constructed physical models and a dedicated neural network-based software. The physical models were designed to model the dispersion mainly in the ultra-low frequency range. The first set of models was used in the training of the software environment, while the second set allowed a complete verification of the technology. Further, the Hilbert transformation was employed to adjust the imaginary components of complex signals and for phase determination. The findings showed that the prototypes are capable of efficient and robust data acquisition, regardless of the applied frequency range, minimizing the impact of measurement errors. Consequently, in in vivo applications, these prototypes minimize the variance of the measurement results, allowing the resulting BIS data to provide a maximum representation of biological phenomena.

show abstract

A Wearable Dual-Channel Bioimpedance Spectrometer for Real-Time Muscle Contraction Detection

Abstract: Manuscript received xx xx, 202x; accepted xx xx, 202x. Date of publication xx xx, 202x; date of current version xx xx, 202x.

Cited by 3 publications

References 46 publications

A Real-Time Muscle Fatigue Detection System Based on Multifrequency EIM and sEMG for Effective NMES

A Real-Time Muscle Fatigue Detection System Based on Multifrequency EIM and sEMG for Effective NMES

Optical Muscle Contraction Detection via Frequency Multiplexed LEDs

An Effective and Robust Parameter Estimation Method in a Self-Developed, Ultra-Low Frequency Impedance Spectroscopy Technique for Large Impedances

Contact Info

Product

Resources

About