Electrical impedance myography (EIM) refers to the specific application of electrical bioimpedance techniques for the assessment of neuromuscular disorders. In EIM, a weak, high-frequency electrical current is applied to a muscle or muscle group of interest and the resulting voltages measured. Among its advantages, the technique can be used noninvasively across a variety of disorders and requires limited subject cooperation and evaluator training to obtain accurate and repeatable data. Studies in both animals and human subjects support its potential utility as a primary diagnostic tool, as well as a biomarker for clinical trial or individual patient use. This review begins by providing an overview of the current state and technological advances in electrical impedance myography and its specific application to the study of muscle. We then provide a summary of the clinical and preclinical applications of EIM for neuromuscular conditions, and conclude with an evaluation of ongoing research efforts and future developments.

Measuring the impedance frequency response of systems by means of frequency sweep electrical impedance spectroscopy (EIS) takes time. An alternative based on broadband signals enables the user to acquire simultaneous impedance response data collection. This is directly reflected in a short measuring time compared to the frequency sweep approach. As a result of this increase in the measuring speed, the accuracy of the impedance spectrum is compromised. The aim of this paper is to study how the choice of the broadband signal can contribute to mitigate this accuracy loss. A review of the major advantages and pitfalls of four different periodic broadband excitations suitable to be used in EIS applications is presented. Their influence on the instrumentation and impedance spectrum accuracy is analyzed. Additionally, the signal processing tools to objectively evaluate the quality of the impedance spectrum are described. In view of the experimental results reported, the impedance spectrum signal-to-noise ratio (SNRZ) obtained with multisine or discrete interval binary sequence signals is about 20–30 dB more accurate than maximum length binary sequence or chirp signals.

The bioimpedance measurement/identification of time-varying biological systems Z(ω, t) by means of electrical impedance spectroscopy (EIS) is still a challenge today. This paper presents a novel measurement and identification approach, the so-called parametric-in-time approach, valid for time-varying (bio-)impedance systems with a (quasi) periodic character. The technique is based on multisine EIS. Contrary to the widely used nonparametric-in-time strategy, the (bio-)impedance Z(ω, t) is assumed to be time-variant during the measurement interval. Therefore, time-varying spectral analysis tools are required. This new parametric-in-time measuring/identification technique has experimentally been validated through three independent sets of in situ measurements of in vivo myocardial impedance. We show that the time-varying myocardial impedance Z(ω, t) is dominantly periodically time varying (PTV), denoted as ZPTV(ω, t). From the temporal analysis of ZPTV(ω, t), we demonstrate that it is possible to decompose ZPTV(ω, t) into a(n) (in)finite sum of fundamental (bio-)impedance spectra, the so-called harmonic impedance spectra (HIS) Zk(ω)s with [Formula: see text]. This is similar to the well-known Fourier series of a periodic signal, but now understood at the level of a periodic system's frequency response. The HIS Zk(ω)s for [Formula: see text] actually summarize in the bi-frequency (ω, k) domain all the temporal in-cycle information about the periodic changes of Z(ω, t). For the particular case k = 0 (i.e. on the ω-axis), Z0(ω) reflects the mean in-cycle behavior of the time-varying bioimpedance. Finally, the HIS Zk(ω)s are directly identified from noisy current and voltage myocardium measurements at the multisine measurement frequencies (i.e. nonparametric-in-frequency).

EIM has been used as a disease severity biomarker in a variety of disorders affecting the muscle, ranging from amyotrophic lateral sclerosis (ALS) to muscular dystrophies to disuse atrophy due to the weightlessness of space. In ALS, studies have demonstrated that major reductions in sample size in clinical trials can be achieved. Similarly, in the Duchenne muscular dystrophy, the technique tracks disease progression and is sensitive to the beneficial effect of steroids. More basic work has demonstrated that EIM can provide a non-invasive means of tracking muscle fiber size. Ongoing innovations include the development of techniques for assessing muscle contraction. EIM is gradually being adopted as a useful, practical, and convenient tool for the assessment of neuromuscular conditions.