Objective: Electrical impedance myography (EIM) measures bioimpedance over muscles. This paper proposes a circuit-based modelling methodology originated from finite element analysis (FEA), to emulate tissues and effects from anthropometric variations, and electrode placements, on EIM measurements. The proposed methodology is demonstrated on the upper arms and lower legs. Methods: FEA evaluates impedance spectra (Z-parameters), sensitivity, and volume impedance density for variations of subcutaneous fat thickness (tf), muscle thickness (tm), and inter-electrode distance (IED), on limb models over 1Hz-1MHz frequency range. The limbs models are based on simplified anatomical data and dielectric properties from published sources. Contributions of tissues to the total impedance are computed from impedance sensitivity and density. FEA Z-parameters are imported into a circuit design environment, and used to develop a three Cole dispersion circuit-based model. FEA and circuit model simulation results are compared with measurements on ten human subjects. Results: Muscle contributions are maximized at 31.25kHz and 62.5kHz for the upper arm and lower leg, respectively, at 4cm IED. The circuit model emulates variations in tf and tm, and simulates up to 89 times faster than FEA. The circuit model matches subjects measurements with RMS errors < 36.43 and < 17.28, while FEA does with < 36.59 and < 4.36. Conclusions: We demonstrate that FEA is able to estimate the optimal frequencies and electrode placements, and circuit-based modelling can accurately emulate the limbs bioimpedance. Significance: The proposed methodology facilitates studying the impact of biophysical principles on EIM, enabling the development of future EIM acquisition systems.

This paper presents a low-distortion current-mode sinusoidal signal generator for bioimpedance spectroscopy measurements. The proposed full current-mode operation enables linearity enhancement and potential savings in silicon area and power consumption. Programmability in the low-pass filter and current driver enables impedance measurements from 0.2 Ω to10 kΩ over a wide frequency range from 1 kHz to 1 MHz.The current generator, designed in a 0.18 μm CMOS process, consumes between 736 μW at the lowest frequency and gain, and 1.70 mW at the highest frequency and gain, and occupies 1.76 mm² silicon area. Post-layout simulation results show a spurious-free dynamic range larger than 40 dBc over the entire frequency range, which enables bioimpedance measurements with errors below 1%, as it is required for wearable devices evaluating neuromuscular disorders.

This paper presents a high input impedance, low-noise, and low-distortion analog front-end (AFE) for bioimpedance (bio-Z) spectroscopy measurements targeting neuromuscular health assessments. The proposed 8-phase quadrature mixer-first architecture achieves a high input impedance through passive mixers driven by non-overlapping clocks. The 8-phase signals are recombined to extract the real and imaginary parts of the bio-Z, while rejecting unwanted harmonics to improve linearity. Programmability of the AFE enables accurate bio-Z measurements up to 10 kΩ for 11 logarithmically spaced frequencies, in the 1 kHz to 1 MHz frequency range. The AFE, designed in a 0.18 μm CMOS process, consumes 245.99 μW at the lowest gain and 300.56 μW at the highest gain, and occupies 2.4 mm2 silicon area. Post-layout simulation results show that the input impedance is always higher than the electrode impedance by more than 10x. The AFE achieves a sensitivity of 7.7 mΩrms, and a maximum SNDR of 103.87 dBFS over a 61 Hz bandwidth. These results demonstrate that the proposed AFE enables bio-Z measurements, using dry electrodes, with errors below 1%.

This paper presents a low-noise bioimpedance (bio-Z) spectroscopy interface for electrical impedance myography (EIM) over the 1 kHz to 2 MHz frequency range. The proposed interface employs a sinusoidal signal generator based on direct-digital-synthesis (DDS) to improve the accuracy of the bio-Z reading, and a quadrature low-intermediate frequency (IF) readout to achieve a good noise-to-power efficiency and the required data throughput to detect muscle contractions. The readout is able to measure baseline and time-varying bio-Z by employing robust and power-efficient low-gain IAs and sixth-order single-bit bandpass (BP) ΔΣ ADCs. The proposed bio-Z spectroscopy interface is implemented in a 180 nm CMOS process, consumes 344.3 - 479.3 μ W, and occupies 5.4 mm 2 area. Measurement results show 0.7 mΩ/√Hz sensitivity at 15.625 kHz, 105.8 dB SNR within 4 Hz bandwidth, and a 146.5 dB figure-of-merit. Additionally, recording of EIM in time and frequency domain during contractions of the bicep brachii muscle demonstrates the potential of the proposed bio-Z interface for wearable EIM systems.

Neuromuscular electrical stimulation (NMES) is a self-directed home based therapeutic tool in early rehabilitation for musculoskeletal (MSK) conditions. However, the effectiveness of traditional NMES is fundamentally constrained by muscle fatigue. To address this limitation, this work proposes a detection system, which simultaneously records multifrequency electrical impedance myography (EIM) and surface electromyography(sEMG) in real time for time-frequency analysis of muscle activation, contraction, and fatigue. To demonstrate the ability to monitor these muscle physiological states, two experiments involving weightless and weighted dynamic contractions of the biceps brachii muscle were performed. Results from these experiments show synchronous changes in sEMG and EIM spectra during contractions, and clear trends in sEMG’s mean power frequency (MPF) and EIM spectra with fatigue progression. Additionally, the configurable 4-channel NMES has been electrically evaluated for clinical use, demonstrating the feasibility of the proposed system for closed-loop stimulation. This work showcases the potential of sEMG and multi-frequency EIM to enhance the effectiveness of NMES for MSK conditions by capturing the behavior of distinct mechanisms of muscle fatigue.