A biomechanics and energetics dataset of neurotypical adults walking with and without kinematic constraints.

Numerous studies have explored the biomechanics and energetics of human walking, offering valuable insights into how we walk. However, prior studies focused on changing external factors (e.g., walking speed) and examined group averages and trends rather than individual adaptations in the presence of internal constraints (e.g., injury-related muscle weakness). To address this gap, this paper presents an open dataset of human walking biomechanics and energetics collected from 21 neurotypical young adults. To investigate the effects of internal constraints (reduced joint range of motion), the participants are both the control group (free walking) and the intervention group (constrained walking - left knee fully extended using a passive orthosis). Each subject walked on a dual-belt treadmill at three speeds (0.4, 0.8, and 1.1 m/s) and five step frequencies ( - 10% to 20% of their preferred frequency) for a total of 30 test conditions. The dataset includes raw and segmented data featuring ground reaction forces, joint motion, muscle activity, and metabolic data. Additionally, a sample code is provided for basic data manipulation and visualisation.

Design, Fabrication and Evaluation of a Stretchable High-Density Electromyography Array.

The adoption of high-density electrode systems for human-machine interfaces in real-life applications has been impeded by practical and technical challenges, including noise interference, motion artefacts and the lack of compact electrode interfaces. To overcome some of these challenges, we introduce a wearable and stretchable electromyography (EMG) array, and present its design, fabrication methodology, characterisation, and comprehensive evaluation. Our proposed solution comprises dry-electrodes on flexible printed circuit board (PCB) substrates, eliminating the need for time-consuming skin preparation. The proposed fabrication method allows the manufacturing of stretchable sleeves, with consistent and standardised coverage across subjects. We thoroughly tested our developed prototype, evaluating its potential for application in both research and real-world environments. The results of our study showed that the developed stretchable array matches or outperforms traditional EMG grids and holds promise in furthering the real-world translation of high-density EMG for human-machine interfaces.

GripAble: Interrater reliability and normative grip strength of UK population.

BACKGROUND: Hand grip strength is an established indicator of individual health status and is used as a biomarker for predicting mortality, disability, and disease risks. GripAble hand grip dynamometer offers a modernized approach to measuring grip strength with its digital and high-accuracy measurement system. PURPOSE: This study aimed to (1) assess the interrater reliability of maximum grip strength (MGS) measurement and (2) establish GripAble's own gender-, age group- and hand-stratified normative MGS reference values of the adult UK population. STUDY DESIGN: Cross-sectional study design. METHODS: Interrater reliability among three raters assessing 30 participants across diverse age groups was measured using the intraclass correlation. In the second study, 11 investigators gathered MGS data from 907 participants across diverse age groups and gender. The average, standard deviation, minimum, median, maximum, and percentiles of MGS were computed for each gender, age group, and hand (L/R). The relationship between MGS and age was examined using quantile regression analysis. Additionally, generalized linear model regression analysis was conducted to explore the influence of participants' demographics (gender, hand [L/R], hand length, hand circumference, age, weight, and height) on MGS. RESULTS: MGS measurements between raters showed excellent agreement (ICC(2,1) = 0.991, 95% confidence interval [0.98, 1.0]). The MGS and age relationship follows a curvilinear pattern, reaching a peak median MGS values of up to 20 kg between 30 and 49 years for females and up to 35 kg between 30 and 59 years for males. Subsequently, MGS declined as age advanced. Gender and hand (L/R) emerged as the primary factors influencing MGS, followed by hand length, hand circumference, age, weight, and height. CONCLUSIONS: The presented normative MGS reference values can be used for interpreting MGS measurements obtained from adults in the United Kingdom using GripAble. This study, along with previous studies on GripAble devices, confirms GripAble as a reliable and valid tool for measuring MGS.

The control of the arm's equilibrium position.

To generate a force, the brain activates muscles that act like springs to pull the arm toward a new equilibrium position. The equilibrium position (EP) is central to our understanding of the biological control of viscoelastic muscles. Although there is evidence of the EP during the control of limb posture, EPs have not been directly identified when the limb exerts a force against the environment. Here, we asked participants to apply a constant force in one of eight directions against a point-like constraint. This constraint was released abruptly to observe the final position to which the arm converged. Importantly, the same force magnitude was maintained while changing the arm's stiffness by modulating the strength of the hand's power grasp. The final position moved further away from the constraint as the arm became less stiff and was inversely proportional to the arm's stiffness, thereby confirming that the final position was the arm's EP. These results demonstrate how the EP changes with the arm's stiffness to produce a desired force in different directions.NEW & NOTEWORTHY According to numerous theories, the brain controls posture and movement by activating muscles that attract the limb toward a so-called equilibrium position, but the universality of this mechanism has not been shown for different motor behaviors. Here, we show that even when pushing or pulling against the environment, the brain achieves the desired force through an equilibrium position that lies beyond the physical constraint.

A systematic investigation of detectors for low signal-to-noise ratio EMG signals.

Background: Active participation of stroke survivors during robot-assisted movement therapy is essential for sensorimotor recovery. Robot-assisted therapy contingent on movement intention is an effective way to encourage patients' active engagement. For severely impaired stroke patients with no residual movements, a surface electromyogram (EMG) has been shown to be a viable option for detecting movement intention. Although numerous algorithms for EMG detection exist, the detector with the highest accuracy and lowest latency for low signal-to-noise ratio (SNR) remains unknown. Methods: This study, therefore, investigates the performance of 13 existing EMG detection algorithms on simulated low SNR (0dB and -3dB) EMG signals generated using three different EMG signal models: Gaussian, Laplacian, and biophysical model. The detector performance was quantified using the false positive rate (FPR), false negative rate (FNR), and detection latency. Any detector that consistently showed FPR and FNR of no more than 20%, and latency of no more than 50ms, was considered an appropriate detector for use in robot-assisted therapy. Results: The results indicate that the Modified Hodges detector - a simplified version of the threshold-based Hodges detector introduced in the current study - was the most consistent detector across the different signal models and SNRs. It consistently performed for ~90% and ~40% of the tested trials for 0dB and -3dB SNR, respectively. The two statistical detectors (Gaussian and Laplacian Approximate Generalized Likelihood Ratio) and the Fuzzy Entropy detectors have a slightly lower performance than Modified Hodges. Conclusions: Overall, the Modified Hodges, Gaussian and Laplacian Approximate Generalized Likelihood Ratio, and the Fuzzy Entropy detectors were identified as the potential candidates that warrant further investigation with real surface EMG data since they had consistent detection performance on low SNR EMG data.

Can Training Make Three Arms Better Than Two Heads for Trimanual Coordination?

Supernumerary effectors have been proposed to enable users to perform tasks alone that normally require assistance from a partner. While various supernumerary robotic limbs have been developed in the last decade, the capability of users to operate them effectively has not yet been proven. Here we tested whether users (i) can complete a task that requires simultaneous and fine control of three effectors, and (ii) can be trained to do so with similar or superior performance as through collaboration with a human partner. As in previous studies, initial augmented capability was less than that of working with a partner. However, one hour of dedicated solo trimanual training across three days significantly increased task performance, so that participants became able to perform trimanual control alone as well as or better than they could with a new partner. This shows the viability of augmentation systems for applications such as in robotic surgery or industrial assembly, which can be further validated on real tasks with physical systems.