Biomechanical Subtasks Research Articles

Exploring storm petrel pattering and sea-anchoring using deep reinforcement learning

Developing hybrid aerial-aquatic vehicles that can interact with water surfaces while remaining aloft is valuable for various tasks, including ecological monitoring, water quality sampling, and search and rescue operations. Storm petrels are a group of pelagic seabirds that exhibit a unique locomotion pattern known as ‘pattering’ or ‘sea-anchoring,’ which is hypothesized to support forward locomotion and/or stationary posture at the water surface. In this study, we use morphological measurements of three storm petrel species and aero/hydrodynamic models to develop a computational storm petrel model and interact it with a hybrid fluid environment. Using deep reinforcement learning algorithms, we find that the storm petrel model exhibits high maneuverability and stability under a wide range of constant wind velocities after training. We also verify in the simulation that the storm petrel can use its ‘pattering’ or ‘sea-anchoring’ behavior to achieve different biomechanical sub-tasks (e.g. weight support, forward locomotion, stabilization) and adapt it under different wind speeds and optimization objectives. Specifically, we observe an adjustment in storm petrel’s movement patterns as wind velocity increases and quantitively analyze its biomechanics underneath. Our results provide new insights into how storm petrels achieve efficient locomotion and dynamic stability at the air–water interface and adapt their behaviors to different wind velocities and tasks in open environments. Ultimately, our study will guide the design of next-generation biomimetic petrel-inspired robots for tasks requiring proximity to the water interface and efficiency.

Age-related changes to triceps surae muscle-subtendon interaction dynamics during walking

Push-off intensity is largely governed by the forces generated by the triceps surae (TS) muscles (gastrocnemius-GAS, soleus-SOL). During walking, the TS muscles undergo different fascicle kinematics and contribute differently to biomechanical subtasks. These differences may be facilitated by the Achilles tendon (AT), which is comprised of subtendons that originate from the TS muscles. We and others have revealed non-uniform displacement patterns within the AT—evidence for sliding between subtendons that may facilitate independent muscle actuation. However, in older adults, we have observed more uniform AT tissue displacements that correlate with reduced push-off intensity. Here, we employed dual-probe ultrasound imaging to investigate TS muscle length change heterogeneity (GAS–SOL) as a determinant of reduced push-off intensity in older adults. Compared to young, older adults walked with more uniform AT tissue displacements and reduced TS muscle length change heterogeneity. These muscle-level differences appeared to negatively impact push-off intensity—evidenced by between-group differences in the extent to which TS muscle length change heterogeneity correlates with mechanical output across walking tasks. Our findings suggest that the capacity for sliding between subtendons may facilitate independent TS muscle actuation in young adults but may restrict that actuation in older adults, likely contributing to reduced push-off intensity.

Muscle Function and Coordination of Amputee Stair Ascent.

Ascending stairs is challenging following transtibial amputation due to the loss of the ankle muscles, which are critical to human movement. Efforts to improve stair ascent following amputation are hindered by limited understanding of how prostheses and remaining muscles contribute to stair ascent. This study developed a three-dimensional muscle-actuated forward dynamics simulation of amputee stair ascent to identify contributions of individual muscles and passive prosthesis to the biomechanical subtasks of stair ascent. The prosthesis was found to provide vertical propulsion throughout stair ascent, similar to non-amputee plantarflexors. However, the timing differed considerably. The prosthesis also contributed to braking, similar to non-amputee soleus, but to a greater extent. In contrast, the prosthesis was unable to replicate the functions of non-amputee gastrocnemius which contributes to forward propulsion during the second half of stance and leg swing initiation. To compensate, hamstrings and vasti of the residual leg increased their contributions to forward propulsion during the first and second halves of stance, respectively. The prosthesis also contributed to medial control, consistent with the non-amputee soleus but not gastrocnemius. Therefore, prosthesis designs that provide additional vertical propulsion as well as forward propulsion, lateral control and leg swing initiation at appropriate points in the gait cycle could improve amputee stair ascent. However, because non-amputee soleus and gastrocnemius contribute oppositely to many subtasks, it may be necessary to couple the prosthesis, which functions most similarly to soleus, with targeted rehabilitation programs focused on muscle groups that can compensate for gastrocnemius.

Muscle Function and Coordination of Stair Ascent

Stair ascent is an activity of daily living and necessary for maintaining independence in community environments. One challenge to improving an individual's ability to ascend stairs is a limited understanding of how lower-limb muscles work in synergy to perform stair ascent. Through dynamic coupling, muscles can perform multiple functions and require contributions from other muscles to perform a task successfully. The purpose of this study was to identify the functional roles of individual muscles during stair ascent and the mechanisms by which muscles work together to perform specific subtasks. A three-dimensional (3D) muscle-actuated simulation of stair ascent was generated to identify individual muscle contributions to the biomechanical subtasks of vertical propulsion, anteroposterior (AP) braking and propulsion, mediolateral control and leg swing. The vasti and plantarflexors were the primary contributors to vertical propulsion during the first and second halves of stance, respectively, while gluteus maximus and hamstrings were the primary contributors to forward propulsion during the first and second halves of stance, respectively. The anterior and posterior components of gluteus medius were the primary contributors to medial control, while vasti and hamstrings were the primary contributors to lateral control during the first and second halves of stance, respectively. To control leg swing, antagonistic muscles spanning the hip, knee, and ankle joints distributed power from the leg to the remaining body segments. These results compliment previous studies analyzing stair ascent and provide further rationale for developing targeted rehabilitation strategies to address patient-specific deficits in stair ascent.

Influence of locomotion speed on biomechanical subtask and muscle synergy

This paper investigates the relationship of biomechanical subtasks, and muscle synergies with various locomotion speeds. Ground reaction force (GRF) of eight healthy subjects is measured synchronously by force plates of treadmill at five different speeds ranging from 0.5m/s to 1.5m/s. Four basic biomechanical subtasks, body support, propulsion, swing, and heel strike preparation, are identified according to GRF. Meanwhile, electromyography (EMG) data, used to extract muscle synergies, are collected from lower limb muscles. EMG signals are segmented periodically based on GRF with the heel strike as the split points. Variability accounted for (VAF) is applied to determine the number of muscle synergies. We find that four muscle synergies can be extracted in all five situations by non-negative matrix factorization (NMF). Furthermore, the four muscle synergies and biomechanical subtasks keep invariant as the walking speed changes.

The influence of locomotor rehabilitation on module quality and post-stroke hemiparetic walking performance

Recent studies have suggested the biomechanical subtasks of walking can be produced by a reduced set of co-excited muscles or modules. Individuals post-stroke often exhibit poor inter-muscular coordination characterized by poor timing and merging of modules that are normally independent in healthy individuals. However, whether locomotor therapy can influence module composition and timing and whether these improvements lead to improved walking performance is unclear. The goal of this study was to examine the influence of a locomotor rehabilitation therapy on module composition and timing and post-stroke hemiparetic walking performance.Twenty-seven post-stroke hemiparetic subjects participated in a 12-week locomotor intervention incorporating treadmill training with body weight support and manual trainers accompanied by training overground walking. Electromyography (EMG), kinematic and ground reaction force data were collected from subjects both pre- and post-therapy and from 19 age-matched healthy controls walking on an instrumented treadmill at their self-selected speed. Non-negative matrix factorization was used to identify the module composition and timing from the EMG data. Module timing and composition, and various measures of walking performance were compared pre- and post-therapy.In subjects with four modules pre- and post-therapy, locomotor training resulted in improved timing of the ankle plantarflexor module and a more extended paretic leg angle that allowed the subjects to walk faster and with more symmetrical propulsion. In addition, subjects with three modules pre-therapy increased their number of modules and improved walking performance post-therapy. Thus, locomotor training has the potential to influence module composition and timing, which can lead to improvements walking performance.

Common muscle synergies for balance and walking

Little is known about the integration of neural mechanisms for balance and locomotion. Muscle synergies have been studied independently in standing balance and walking, but not compared. Here, we hypothesized that reactive balance and walking are mediated by a common set of lower-limb muscle synergies. In humans, we examined muscle activity during multidirectional support-surface perturbations during standing and walking, as well as unperturbed walking at two speeds. We show that most muscle synergies used in perturbations responses during standing were also used in perturbation responses during walking, suggesting common neural mechanisms for reactive balance across different contexts. We also show that most muscle synergies using in reactive balance were also used during unperturbed walking, suggesting that neural circuits mediating locomotion and reactive balance recruit a common set of muscle synergies to achieve task-level goals. Differences in muscle synergies across conditions reflected differences in the biomechanical demands of the tasks. For example, muscle synergies specific to walking perturbations may reflect biomechanical challenges associated with single limb stance, and muscle synergies used during sagittal balance recovery in standing but not walking were consistent with maintaining the different desired center of mass motions in standing vs. walking. Thus, muscle synergies specifying spatial organization of muscle activation patterns may define a repertoire of biomechanical subtasks available to different neural circuits governing walking and reactive balance and may be recruited based on task-level goals. Muscle synergy analysis may aid in dissociating deficits in spatial vs. temporal organization of muscle activity in motor deficits. Muscle synergy analysis may also provide a more generalizable assessment of motor function by identifying whether common modular mechanisms are impaired across the performance of multiple motor tasks.

Three-dimensional modular control of human walking

Recent studies have suggested that complex muscle activity during walking may be controlled using a reduced neural control strategy organized around the co-excitation of multiple muscles, or modules. Previous computer simulation studies have shown that five modules satisfy the sagittal-plane biomechanical sub-tasks of 2D walking. The present study shows that a sixth module, which contributes primarily to mediolateral balance control and contralateral leg swing, is needed to satisfy the additional non-sagittal plane demands of 3D walking. Body support was provided by Module 1 (hip and knee extensors, hip abductors) in early stance and Module 2 (plantarflexors) in late stance. In early stance, forward propulsion was provided by Module 4 (hamstrings), but net braking occurred due to Modules 1 and 2. Forward propulsion was provided by Module 2 in late stance. Module 1 accelerated the body medially throughout stance, dominating the lateral acceleration in early stance provided by Modules 4 and 6 (adductor magnus) and in late stance by Module 2, except near toe-off. Modules 3 (ankle dorsiflexors, rectus femoris) and 5 (hip flexors and adductors except adductor magnus) accelerated the ipsilateral leg forward in early swing whereas Module 4 decelerated the ipsilateral leg prior to heel-strike. Finally, Modules 1, 4 and 6 accelerated the contralateral leg forward prior to and during contralateral swing. Since the modules were based on experimentally measured muscle activity, these results provide further evidence that a simple neural control strategy involving muscle activation modules organized around task-specific biomechanical functions may be used to control complex human movements.

Muscle Synergies: Implications for Clinical Evaluation and Rehabilitation of Movement

We present a method called muscle synergy analysis, which can offer clinicians insight into both underlying neural strategies for movement and functional outcomes of muscle activity. Although neural dysfunction is central to many motor deficits, neural activity during movements is not directly measurable. Consequently, the majority of clinical tests focus on evaluating motor outputs at the behavioral and kinematic levels. However, altered behavioral or kinematic outcomes could be the result of multiple distinct neural abnormalities with very different muscle coordination patterns. Because muscle activity reflects motoneuron activity and generates the forces that produce behavioral outcomes, an analysis of muscle activity may provide a better understanding of the functional neural deficits in the impaired nervous system. Unfortunately electromyographic datasets can be large, highly variable, and difficult to interpret, precluding their clinical utility. Computational analyses can be used to extract muscle synergies from such datasets, revealing underlying patterns that may reflect different levels of neural function. These muscle synergies are hypothesized to represent motor modules recruited by the nervous system to flexibly perform biomechanical subtasks necessary for movement. For example, hemiparetic stroke patients exhibit differences in the number of muscle synergies, which may reflect disruptions in descending neural pathways and are correlated to deficits in motor function. Muscle synergy analysis may thus offer the clinician a better view of the neural structure underlying motor behaviors and how they change in motor deficits and rehabilitation. Such information could inform diagnostic tools and evidence-based interventions specifically targeted to a patient's deficits.

Modular control of human walking: Adaptations to altered mechanical demands

Studies have suggested that the nervous system may adopt a control scheme in which synergistic muscle groups are controlled by common excitation patters, or modules, to simplify the coordination of movement tasks such as walking. A recent computer modeling and simulation study of human walking using experimentally derived modules as the control inputs provided evidence that individual modules are associated with specific biomechanical subtasks, such as generating body support and forward propulsion. The present study tests whether the modules identified during normal walking could produce simulations of walking when the mechanical demands were substantially altered. Walking simulations were generated that emulated human subjects who had their body weight and/or body mass increased and decreased by 25%. By scaling the magnitude of five module patterns, the simulations could emulate the subjects’ response to each condition by simply scaling the mechanical output from modules associated with specific biomechanical subtasks. Specifically, the modules associated with providing body support increased (decreased) their contribution to the vertical ground reaction force when body weight was increased (decreased) and the module associated with providing forward propulsion increased its contribution to the positive anterior–posterior ground reaction force and positive trunk power when the body mass was increased. The modules that contribute to controlling leg swing were unaffected by the perturbations. These results support the idea that the nervous system may use a modular control strategy and that flexible modulation of module recruitment intensity may be sufficient to meet large changes in mechanical demand.

Modular control of human walking: A simulation study

Recent evidence suggests that performance of complex locomotor tasks such as walking may be accomplished using a simple underlying organization of co-active muscles, or “modules”, which have been assumed to be structured to perform task-specific biomechanical functions. However, no study has explicitly tested whether the modules would actually produce the biomechanical functions associated with them or even produce a well-coordinated movement. In this study, we generated muscle-actuated forward dynamics simulations of normal walking using muscle activation modules (identified using non-negative matrix factorization) as the muscle control inputs to identify the contributions of each module to the biomechanical sub-tasks of walking (i.e., body support, forward propulsion, and leg swing). The simulation analysis showed that a simple neural control strategy involving five muscle activation modules was sufficient to perform the basic sub-tasks of walking. Module 1 (gluteus medius, vasti, and rectus femoris) primarily contributed to body support in early stance while Module 2 (soleus and gastrocnemius) contributed to both body support and propulsion in late stance. Module 3 (rectus femoris and tibialis anterior) acted to decelerate the leg in early and late swing while generating energy to the trunk throughout swing. Module 4 (hamstrings) acted to absorb leg energy (i.e., decelerate it) in late swing while increasing the leg energy in early stance. Post-hoc analysis revealed an additional module (Module 5: iliopsoas) acted to accelerate the leg forward in pre- and early swing. These results provide evidence that the identified modules can act as basic neural control elements that generate task-specific biomechanical functions to produce well-coordinated walking.