Walking Bout Detection for People Living in Long Residential Care: A Computationally Efficient Algorithm for a 3-Axis Accelerometer on the Lower Back.

Accurate and reliable measurement of real-world walking activity is clinically relevant, particularly for people with mobility difficulties. Insights on walking can help understand mobility function, disease progression, and fall risks. People living in long-term residential care environments have heterogeneous and often pathological walking patterns, making it difficult for conventional algorithms paired with wearable sensors to detect their walking activity. We designed two walking bout detection algorithms for people living in long-term residential care. Both algorithms used thresholds on the magnitude of acceleration from a 3-axis accelerometer on the lower back to classify data as "walking" or "non-walking". One algorithm had generic thresholds, whereas the other used personalized thresholds. To validate and evaluate the algorithms, we compared the classifications of walking/non-walking from our algorithms to the real-time research assistant annotated labels and the classification output from an algorithm validated on a healthy population. Both the generic and personalized algorithms had acceptable accuracy (0.83 and 0.82, respectively). The personalized algorithm showed the highest specificity (0.84) of all tested algorithms, meaning it was the best suited to determine input data for gait characteristic extraction. The developed algorithms were almost 60% quicker than the previously developed algorithms, suggesting they are adaptable for real-time processing.

Tapping Into Skeletal Muscle Biomechanics for Design and Control of Lower Limb Exoskeletons: A Narrative Review.

Lower limb exoskeletons and exosuits ("exos") are traditionally designed with a strong focus on mechatronics and actuation, whereas the "human side" is often disregarded or minimally modeled. Muscle biomechanics principles and skeletal muscle response to robot-delivered loads should be incorporated in design/control of exos. In this narrative review, we summarize the advances in literature with respect to the fusion of muscle biomechanics and lower limb exoskeletons. We report methods to measure muscle biomechanics directly and indirectly and summarize the studies that have incorporated muscle measures for improved design and control of intuitive lower limb exos. Finally, we delve into articles that have studied how the human-exo interaction influences muscle biomechanics during locomotion. To support neurorehabilitation and facilitate everyday use of wearable assistive technologies, we believe that future studies should investigate and predict how exoskeleton assistance strategies would structurally remodel skeletal muscle over time. Real-time mapping of the neuromechanical origin and generation of muscle force resulting in joint torques should be combined with musculoskeletal models to address time-varying parameters such as adaptation to exos and fatigue. Development of smarter predictive controllers that steer rather than assist biological components could result in a synchronized human-machine system that optimizes the biological and electromechanical performance of the combined system.

Modeling and Stiffness-based Continuous Torque Control of Lightweight Quasi-Direct-Drive Knee Exoskeletons for Versatile Walking Assistance.

State-of-the-art exoskeletons are typically limited by low control bandwidth and small range stiffness of actuators which are based on high gear ratios and elastic components (e.g., series elastic actuators). Furthermore, most exoskeletons are based on discrete gait phase detection and/or discrete stiffness control resulting in discontinuous torque profiles. To fill these two gaps, we developed a portable lightweight knee exoskeleton using quasi-direct drive (QDD) actuation that provides 14 Nm torque (36.8% biological joint moment for overground walking). This paper presents 1) stiffness modeling of torque-controlled QDD exoskeletons and 2) stiffness-based continuous torque controller that estimates knee joint moment in real-time. Experimental tests found the exoskeleton had high bandwidth of stiffness control (16 Hz under 100 Nm/rad) and high torque tracking accuracy with 0.34 Nm Root Mean Square (RMS) error (6.22%) across 0-350 Nm/rad large range stiffness. The continuous controller was able to estimate knee moments accurately and smoothly for three walking speeds and their transitions. Experimental results with 8 able-bodied subjects demonstrated that our exoskeleton was able to reduce the muscle activities of all 8 measured knee and ankle muscles by 8.60%-15.22% relative to unpowered condition, and two knee flexors and one ankle plantar flexor by 1.92%-10.24% relative to baseline (no exoskeleton) condition.

Energetics of Walking With a Robotic Knee Exoskeleton.

The authors tested 4 young healthy subjects walking with a powered knee exoskeleton to determine if it could reduce the metabolic cost of locomotion. Subjects walked with a backpack loaded and unloaded, on a treadmill with inclinations of 0° and 15°, and outdoors with varied natural terrain. Participants walked at a self-selected speed (average 1.0 m/s) for all conditions, except incline treadmill walking (average 0.5 m/s). The authors hypothesized that the knee exoskeleton would reduce the metabolic cost of walking uphill and with a load compared with walking without the exoskeleton. The knee exoskeleton reduced metabolic cost by 4.2% in the 15° incline with the backpack load. All other conditions had an increase in metabolic cost when using the knee exoskeleton compared with not using the exoskeleton. There was more variation in metabolic cost over the outdoor walking course with the knee exoskeleton than without it. Our findings indicate that powered assistance at the knee is more likely to decrease the metabolic cost of walking in uphill conditions and during loaded walking rather than in level conditions without a backpack load. Differences in positive mechanical work demand at the knee for varying conditions may explain the differences in metabolic benefit from the exoskeleton.

EMG-informed neuromuscular model assesses the effects of varied bodyweight support on muscles during overground walking.

Bodyweight supported walking is a common gait rehabilitation method that can be used as an experimental approach to better understand walking biomechanics. Neuromuscular modeling can provide an analytical means to gain insight into how muscles coordinate to produce walking and other movements. To better understand how muscle length and velocity affect muscle force during overground walking with bodyweight support, we used an electromyography (EMG)-informed neuromuscular model to investigate changes in muscle parameters (muscle force, activation and fiber length) at varying bodyweight support levels: 0%, 24%, 45% and 69% bodyweight. Coupled constant force springs provided a vertical support force while we collected biomechanical data (EMG, motion capture and ground reaction forces) from healthy, neurologically intact participants walking at 1.20 ± 0.06 m/s. The lateral and medial gastrocnemius demonstrated a significant decrease in muscle force (lateral: p = 0.002 and medial: p < 0.001) and activation (lateral: p = 0.007 and medial: p < 0.001) through push-off at higher levels of support. The soleus, in contrast, had no significant change in muscle activation through push-off (p = 0.652) regardless of bodyweight support level even though soleus muscle force decreased with increasing support (p < 0.001). During push-off, the soleus had shorter muscle fiber lengths and faster shortening velocities as bodyweight support levels increased. These results provide insight into how muscle force can be decoupled from effective bodyweight during bodyweight supported walking due to changes in muscle fiber dynamics. The findings contribute evidence that clinicians and biomechanists should not expect a reduction in muscle activation and force when using bodyweight support to assist gait during rehabilitation.

Effects of simulated reduced gravity and walking speed on ankle, knee, and hip quasi-stiffness in overground walking.

Quasi-stiffness characterizes the dynamics of a joint in specific sections of stance-phase and is used in the design of wearable devices to assist walking. We sought to investigate the effect of simulated reduced gravity and walking speed on quasi-stiffness of the hip, knee, and ankle in overground walking. 12 participants walked at 0.4, 0.8, 1.2, and 1.6 m/s in 1, 0.76, 0.54, and 0.31 gravity. We defined 11 delimiting points in stance phase (4 each for the ankle and hip, 3 for the knee) and calculated the quasi-stiffness for 4 phases for both the hip and ankle, and 2 phases for the knee. The R2 value quantified the suitability of the quasi-stiffness models. We found gravity level had a significant effect on 6 phases of quasi-stiffness, while speed significantly affected the quasi-stiffness in 5 phases. We concluded that the intrinsic muscle-tendon unit stiffness was the biggest determinant of quasi-stiffness. Speed had a significant effect on the R2 of all phases of quasi-stiffness. Slow walking (0.4 m/s) was the least accurately modelled walking speed. Our findings showed adaptions in gait strategy when relative power and strength of the joints were increased in low gravity, which has implications for prosthesis and exoskeleton design.

Human muscle activity and lower limb biomechanics of overground walking at varying levels of simulated reduced gravity and gait speeds.

Reducing the mechanical load on the human body through simulated reduced gravity can reveal important insight into locomotion biomechanics. The purpose of this study was to quantify the effects of simulated reduced gravity on muscle activation levels and lower limb biomechanics across a range of overground walking speeds. Our overall hypothesis was that muscle activation amplitudes would not decrease proportionally to gravity level. We recruited 12 participants (6 female, 6 male) to walk overground at 1.0, 0.76, 0.55, and 0.31 G for four speeds: 0.4, 0.8, 1.2, and 1.6 ms-1. We found that peak ground reaction forces, peak knee extension moment in early stance, peak hip flexion moment, and peak ankle extension moment all decreased substantially with reduced gravity. The peak knee extension moment at late stance/early swing did not change with gravity. The effect of gravity on muscle activity amplitude varied considerably with muscle and speed, often varying nonlinearly with gravity level. Quadriceps (rectus femoris, vastus lateralis, & vastus medialis) and medial gastrocnemius activity decreased in stance phase with reduced gravity. Soleus and lateral gastrocnemius activity had no statistical differences with gravity level. Tibialis anterior and biceps femoris increased with simulated reduced gravity in swing and stance phase, respectively. The uncoupled relationship between simulated gravity level and muscle activity have important implications for understanding biomechanical muscle functions during human walking and for the use of bodyweight support for gait rehabilitation after injury.

Design and Validation of a Low-Cost Bodyweight Support System for Overground Walking.

Walking with bodyweight support is a vital tool for both gait rehabilitation and biomechanics research. There are few commercially available bodyweight support systems for overground walking that are able to provide a near constant lifting force of more than 50% bodyweight. The devices that do exist are expensive and are not often used outside of rehabilitation clinics. Our aim was to design, build, and validate a bodyweight support device for overground walking that: (1) cost less than $5000, (2) could support up to 75% of the users' bodyweight (BW), and (3) had small (±5% BW) fluctuations in force. We used pairs of constant force springs to provide the constant lifting force. To validate the force fluctuation, we recruited eight participants to walk at 0.4, 0.8, 1.2, and 1.6 m/s with 0%, 22%, 46%, and 69% of their bodyweight supported. We used a load cell to measure force through the system and motion capture data to create a vector of the supplied lifting force. The final prototype cost less than $4000 and was able to support 80% of the users' bodyweight. Fluctuations in vertical force increased with speed and bodyweight support, reaching a maximum of 10% at 1.6 m/s and 69% BW support.