Publications

INTRODUCTION/AIMS: This study examined the potential of multi-frequency electrical impedance myography (EIM) to predict hand grip strength (HGS) variability among adults, including a large proportion of older adults, with and without sarcopenia. The objective was to develop predictive models using EIM data for assessing HGS and to explore its potential use in clinical evaluations of muscle function.

METHODS: Seventy-three participants aged 18-93 years were recruited at community events, with 69 completing EIM and HGS assessments. EIM data were collected from the forearm flexor and extensor muscle groups, and regression techniques, including Lasso regression, were applied to develop predictive models.

RESULTS: Approximately 60% of participants were over 65 years old, and 23% exhibited HGS values below sarcopenia thresholds. EIM measurements explained 48% of the variance in HGS. Adding demographic factors (sex, age, BMI) improved the explained variance to 64%, highlighting EIM's potential in muscle health assessments.

DISCUSSION: The findings suggest that multi-frequency EIM shows potential as a non-invasive tool for predicting HGS and assessing muscle function, particularly in aging populations. Further research is needed to fully establish EIM's utility in clinical settings for the early detection and management of sarcopenia.

What do Charles Darwin, T.H. Huxley, August Krogh and Charles Sherrington have in common? Florence Buchanan - a name history has unjustly dimmed but never erased. Her academic lineage is a direct thread through the titans of biology: E. Ray Lankester mentored her after being shaped by Huxley, Darwin's celebrated protégé. Buchanan's early career flourished under the mentorship of John Scott Burdon-Sanderson, but it was as an independent scientist that she collaborated with Nobel laureates Krogh and Sherrington, cementing her place among the greatest physiologists of her era. While accolades marked her career - a doctor of science, prestigious fellowships and groundbreaking publications - her path was anything but easy. As the first woman to attend meetings of The Physiological Society, she broke barriers but faced systemic exclusions, barred from The Society's dinners where scientific relationships were forged. Buchanan's meticulous experiments revealed muscles' intrinsic electrical rhythms and reshaped how physiology understands the neural control of the heart. Though her contributions were celebrated in her time, they were often overshadowed by her male colleagues. Who was this trailblazer whose scientific rigor and resilience quietly shaped modern physiology?

Kieser, J, Langford, M, Stover, E, Tomkinson, GR, Clark, BC, Cawthon, PM, and McGrath, R. Absolute agreement between subjective hand squeeze and objective handgrip strength in adults. J Strength Cond Res 39(1): 16-23, 2025-Despite handgrip strength (HGS) being considered a convenient muscle strength assessment, HGS lacks routine measurement in sports medicine and healthcare settings because barriers such as time and lack of instrumentation may exist. Alternatives to circumvent these barriers should be sought. This study examined the absolute agreement of a subjective estimate of strength capacity on objectively measured HGS in adults aged 18-84 years. We also evaluated the test-retest reliability of an electronic handgrip dynamometer as a secondary purpose. There were 4 trained interviewers (i.e., assessors) who were assigned completely at random to subject laboratory visits occurring on 2 separate days. Trained interviewers carefully positioned their fingers into the hand of each subject before asking them to squeeze their fingers with maximal effort, and interviewers estimated each subject's HGS. An electronic handgrip dynamometer objectively measured HGS. Intraclass correlation coefficients (ICCs) were used for the analyses. The analytic sample included 100 subjects (age: 48.0 ± 20.2 years; 61% women). Poor agreement between mean objective HGS and averaged subjective hand squeeze was observed (ICC: 0.47; 95% confidence interval [CI]: 0.40-0.53). However, there was moderate agreement between dynamometer-derived maximal HGS and the most accurate HGS estimate (ICC: 0.75; CI: 0.65-0.86). An excellent test-retest reliability was found for mean (ICC: 0.97; CI: 0.95-0.98) and maximal HGS with the electronic dynamometer (ICC: 0.97; CI: 0.96-0.98). Trained interviewers performing subjective hand squeezes can approximate objective HGS with adequate accuracy, which could be useful when time and handgrip dynamometry access are lacking. Expanded interviewer training and testing may help with implementation.

Humans adapt their locomotion seamlessly in response to changes in the body or the environment. It is unclear how such adaptation improves performance measures like energy consumption or symmetry while avoiding falling. Here, we model locomotor adaptation as interactions between a stabilizing controller that reacts quickly to perturbations and a reinforcement learner that gradually improves the controller's performance through local exploration and memory. This model predicts time-varying adaptation in many settings: walking on a split-belt treadmill (i.e. with both feet at different speeds), with asymmetric leg weights, or using exoskeletons - capturing learning and generalization phenomena in ten prior experiments and two model-guided experiments conducted here. The performance measure of energy minimization with a minor cost for asymmetry captures a broad range of phenomena and can act alongside other mechanisms such as reducing sensory prediction error. Such a model-based understanding of adaptation can guide rehabilitation and wearable robot control.