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1. Upper Extremity Muscle Activation Pattern Prediction Through Synergy Extrapolation and Electromyography-Driven Modeling

   https://doi.org/10.1115/1.4063899  

   Tahmid, Shadman; Font-Llagunes, Josep M; Yang, James (January 2024, Journal of Biomechanical Engineering)

   Abstract Patients with neuromuscular disease fail to produce necessary muscle force and have trouble maintaining joint moment required to perform activities of daily living. Measuring muscle force values in patients with neuromuscular disease is important but challenging. Electromyography (EMG) can be used to obtain muscle activation values, which can be converted to muscle forces and joint torques. Surface electrodes can measure activations of superficial muscles, but fine-wire electrodes are needed for deep muscles, although it is invasive and require skilled personnel and preparation time. EMG-driven modeling with surface electrodes alone could underestimate the net torque. In this research, authors propose a methodology to predict muscle activations from deeper muscles of the upper extremity. This method finds missing muscle activation one at a time by combining an EMG-driven musculoskeletal model and muscle synergies. This method tracks inverse dynamics joint moments to determine synergy vector weights and predict muscle activation of selected shoulder and elbow muscles of a healthy subject. In addition, muscle-tendon parameter values (optimal fiber length, tendon slack length, and maximum isometric force) have been personalized to the experimental subject. The methodology is tested for a wide range of rehabilitation tasks of the upper extremity across multiple healthy subjects. Results show this methodology can determine single unmeasured muscle activation up to Pearson's correlation coefficient (R) of 0.99 (root mean squared error, RMSE = 0.001) and 0.92 (RMSE = 0.13) for the elbow and shoulder muscles, respectively, for one degree-of-freedom (DoF) tasks. For more complicated five DoF tasks, activation prediction accuracy can reach up to R = 0.71 (RMSE = 0.29). 

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2. In vivo estimation of anisotropic mechanical properties of the gastrocnemius during functional loading with MR elastography

   https://doi.org/10.1088/1361-6560/acb482  

   Smith, Daniel R; Caban-Rivera, Diego A; Williams, L Tyler; Van_Houten, Elijah_E W; Bayly, Phil V; Paulsen, Keith D; McGarry, Matthew_D J; Johnson, Curtis L (February 2023, Physics in Medicine & Biology)

   Abstract Objective.In vivoimaging assessments of skeletal muscle structure and function allow for longitudinal quantification of tissue health. Magnetic resonance elastography (MRE) non-invasively quantifies tissue mechanical properties, allowing for evaluation of skeletal muscle biomechanics in response to loading, creating a better understanding of muscle functional health.Approach. In this study, we analyze the anisotropic mechanical response of calf muscles using MRE with a transversely isotropic, nonlinear inversion algorithm (TI-NLI) to investigate the role of muscle fiber stiffening under load. We estimate anisotropic material parameters including fiber shear stiffness ( ${\mu }_1$), substrate shear stiffness ( ${\mu }_2$), shear anisotropy ( $\varphi$), and tensile anisotropy ( $\zeta$) of the gastrocnemius muscle in response to both passive and active tension.Main results. In passive tension, we found a significant increase in ${\mu }_1,$ $\varphi ,$and $\zeta$with increasing muscle length. While in active tension, we observed increasing ${\mu }_2$and decreasing $\varphi$and $\zeta$during active dorsiflexion and plantarflexion—indicating less anisotropy—with greater effects when the muscles act as agonist.Significance. The study demonstrates the ability of this anisotropic MRE method to capture the multifaceted mechanical response of skeletal muscle to tissue loading from muscle lengthening and contraction. 

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3. Increasing Electrical Muscle Stimulation's Dexterity by means of Back of the Hand Actuation

   https://doi.org/10.1145/3411764.3445761  

   Takahashi, Akifumi; Brooks, Jas; Kajimoto, Hiroyuki; Lopes, Pedro (May 2021, CHI Conference on Human Factors in Computing Systems)

   We propose a technique that allows an unprecedented level of dexterity in electrical muscle stimulation (EMS), i.e., it allows interactive EMS-based devices to flex the user's fingers independently of each other. EMS is a promising technique for force feedback because of its small form factor when compared to mechanical actuators. However, the current EMS approach to flexing the user's fingers (i.e., attaching electrodes to the base of the forearm, where finger muscles anchor) is limited by its inability to flex a target finger's metacarpophalangeal (MCP) joint independently of the other fingers. In other words, current EMS devices cannot flex one finger alone, they always induce unwanted actuation to adjacent fingers. To tackle the lack of dexterity, we propose and validate a new electrode layout that places the electrodes on the back of the hand, where they stimulate the interossei/lumbricals muscles in the palm, which have never received attention with regards to EMS. In our user study, we found that our technique offers four key benefits when compared to existing EMS electrode layouts: our technique (1) flexes all four fingers around the MCP joint more independently; (2) has less unwanted flexion of other joints (such as the proximal interphalangeal joint); (3) is more robust to wrist rotations; and (4) reduces calibration time. Therefore, our EMS technique enables applications for interactive EMS systems that require a level of flexion dexterity not available until now. We demonstrate the improved dexterity with four example applications: three musical instrumental tutorials (piano, drum, and guitar) and a VR application that renders force feedback in individual fingers while manipulating a yo-yo. 

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4. The importance of comparative physiology: mechanisms, diversity and adaptation in skeletal muscle physiology and mechanics

   https://doi.org/10.1242/jeb.245158  

   Mendoza, E.; Moen, D. S.; Holt, N. C. (April 2023, Journal of Experimental Biology)

   ABSTRACT Skeletal muscle powers animal movement, making it an important determinant of fitness. The classic excitation–contraction coupling, sliding-filament and crossbridge theories are thought to describe the processes of muscle activation and the generation of force, work and power. Here, we review how the comparative, realistic muscle physiology typified by Journal of Experimental Biology over the last 100 years has supported and refuted these theories. We examine variation in the contraction rates and force–length and force–velocity relationships predicted by these theories across diverse muscles, and explore what has been learnt from the use of workloop and force-controlled techniques that attempt to replicate aspects of in vivo muscle function. We suggest inclusion of features of muscle contraction not explained by classic theories in our routine characterization of muscles, and the use of phylogenetic comparative methods to allow exploration of the effects of factors such as evolutionary history, ecology, behavior and size on muscle physiology and mechanics. We hope that these future directions will improve our understanding of the mechanisms of muscle contraction, allow us to better characterize the variation in muscle performance possible, and enable us to infer adaptation. 

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5. Upper Extremity Joint Torque Estimation Through an Electromyography-Driven Model

   https://doi.org/10.1115/1.4056255  

   Tahmid, Shadman; Font-Llagunes, Josep M.; Yang, James (June 2023, Journal of Computing and Information Science in Engineering)

   Abstract Cerebrovascular accidents like a stroke can affect the lower limb as well as upper extremity joints (i.e., shoulder, elbow, or wrist) and hinder the ability to produce necessary torque for activities of daily living. In such cases, muscles’ ability to generate forces reduces, thus affecting the joint’s torque production. Understanding how muscles generate forces is a key element to injury detection. Researchers have developed several computational methods to obtain muscle forces and joint torques. Electromyography (EMG) driven modeling is one of the approaches to estimate muscle forces and obtain joint torques from muscle activity measurements. Musculoskeletal models and EMG-driven models require necessary muscle-specific parameters for the calculation. The focus of this study is to investigate the EMG-driven approach along with an upper extremity musculoskeletal model to determine muscle forces of two major muscle groups, biceps brachii and triceps brachii, consisting of seven muscle-tendon units. Estimated muscle forces are used to determine the elbow joint torque. Experimental EMG signals and motion capture data are collected for a healthy subject. The musculoskeletal model is scaled to match the geometric parameters of the subject. Then, the approach calculates muscle forces and joint moment for two tasks: simple elbow flexion extension and triceps kickback. Individual muscle forces and net joint torques for both tasks are estimated. The study also has compared the effect of muscle-tendon parameters (optimal fiber length and tendon slack length) on the estimated results. 

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