Evaluating Electromyography and Sonomyography Sensor Fusion to Estimate Lower-Limb Kinematics Using Gaussian Process Regression.

Research on robotic lower-limb assistive devices over the past decade has generated autonomous, multiple degree-of-freedom devices to augment human performance during a variety of scenarios. However, the increase in capabilities of these devices is met with an increase in the complexity of the overall control problem and requirement for an accurate and robust sensing modality for intent recognition. Due to its ability to precede changes in motion, surface electromyography (EMG) is widely studied as a peripheral sensing modality for capturing features of muscle activity as an input for control of powered assistive devices. In order to capture features that contribute to muscle contraction and joint motion beyond muscle activity of superficial muscles, researchers have introduced sonomyography, or real-time dynamic ultrasound imaging of skeletal muscle. However, the ability of these sonomyography features to continuously predict multiple lower-limb joint kinematics during widely varying ambulation tasks, and their potential as an input for powered multiple degree-of-freedom lower-limb assistive devices is unknown. The objective of this research is to evaluate surface EMG and sonomyography, as well as the fusion of features from both sensing modalities, as inputs to Gaussian process regression models for the continuous estimation of hip, knee and ankle angle and velocity during level walking, stair ascent/descent and ramp ascent/descent ambulation. Gaussian process regression is a Bayesian nonlinear regression model that has been introduced as an alternative to musculoskeletal model-based techniques. In this study, time-intensity features of sonomyography on both the anterior and posterior thigh along with time-domain features of surface EMG from eight muscles on the lower-limb were used to train and test subject-dependent and task-invariant Gaussian process regression models for the continuous estimation of hip, knee and ankle motion. Overall, anterior sonomyography sensor fusion with surface EMG significantly improved estimation of hip, knee and ankle motion for all ambulation tasks (level ground, stair and ramp ambulation) in comparison to surface EMG alone. Additionally, anterior sonomyography alone significantly improved errors at the hip and knee for most tasks compared to surface EMG. These findings help inform the implementation and integration of volitional control strategies for robotic assistive technologies.

Effect of Neuromuscular Electrical Stimulation During Walking on Pain Sensitivity in Women With Obesity With Knee Pain: A Randomized Controlled Trial.

OBJECTIVE: To assess the extent to which pain sensitivity is altered in women with obesity with frequent knee symptoms who walk with either a hybrid training system (HTS) that provides antagonist muscle electrical stimulation vs sensory transcutaneous electrical nerve stimulation (TENS). DESIGN: Randomized, double-blinded, controlled trial. SETTING: University-based fitness center. PARTICIPANTS: Twenty-eight women (N=28) with obesity, aged 40-70 years, with daily knee symptoms. INTERVENTIONS: Participants were randomized to 12 weeks of biweekly 30-minute walking exercise with either HTS (HTSW group) or sensory TENS (control group). MAIN OUTCOME MEASURES: Pressure pain thresholds (PPTs) at the more symptomatic knee (local PPT) and PPT at the ipsilateral pain-free wrist (remote PPT). RESULTS: After adjustment for preintervention values and body mass index (BMI), there was a statistically significant improvement in local PPT in the HTSW group compared with the control group (P=.039). After adjustment for pretraining value, age, and BMI, changes in remote PPT when comparing groups did not reach statistical significance, although the HTS group tended to demonstrate increased remote PPT (P=.052) compared with the control group. Moreover, after adjustment for pretraining value, knee pain, and quality of life, comparing groups did not reach statistical significance, although the HTS group tended to demonstrate decreased knee pain (P=.069) compared with the control group. CONCLUSIONS: Augmentation of walking exercise with HTS was more effective than application of sensory TENS in improving local pain sensitivity at the knee but not at the wrist in women with obesity with frequent knee symptoms.

Longitudinal Relationship Between Tibiofemoral Contact Stress at Baseline and Worsening of Knee Pain Over 84 Months in the Multicenter Osteoarthritis Study.

OBJECTIVE: The aim of the study was to determine whether tibiofemoral contact stress predicts risk for worsening knee pain over 84 ms in adults aged 50-79 yrs with or at elevated risk for knee osteoarthritis. DESIGN: Baseline tibiofemoral contact stress was estimated using discrete element analysis. Other baseline measures included weight, height, hip-knee-ankle alignment, Kellgren-Lawrence grade, and Western Ontario and McMaster Universities Osteoarthritis Index pain subscale. Logistic regression models assessed the association between baseline contact stress and 84-mo worsening of Western Ontario and McMaster Universities Osteoarthritis Index pain subscale. RESULTS: Data from the dominant knee (72.6% Kellgren-Lawrence grade 0/1 and 27.4% Kellgren-Lawrence grade ≥ 2) of 208 participants (64.4% female, mean ± SD body mass index = 29.6 ± 5.1 kg/m 2 ) were analyzed. Baseline mean and peak contact stress were 3.3 ± 0.9 and 9.4 ± 4.3 MPa, respectively. Forty-seven knees met the criterion for worsening pain. The highest tertiles in comparison with the lowest tertiles of mean (odds ratio [95% confidence interval] = 2.47 [1.03-5.95], P = 0.04) and peak (2.49 [1.03-5.98], P = 0.04) contact stress were associated with worsening pain at 84 mos, after adjustment for age, sex, race, clinic site, and baseline pain. Post hoc sensitivity analyses including adjustment for body mass index and hip-knee-ankle alignment attenuated the effect. CONCLUSIONS: These findings suggest that elevated tibiofemoral contact stress can predict the development of worsening of knee pain.

Ultrasound-Derived Features of Muscle Architecture Provide Unique Temporal Characterization of Volitional Knee Motion.

Sonomyography, or dynamic ultrasound imaging of skeletal muscle, has gained significant interest in rehabilitation medicine. Previously, correlations relating sonomyography features of muscle contraction, including muscle thickness, pennation angle, angle between aponeuroses and fascicle length, to muscle force production, strength and joint motion have been established. Additionally, relationships between grayscale image intensity, or echogenicity, with maximum voluntary isometric contraction of muscle have been noted. However, the time relationship between changes in various sonomyography features during volitional motion has yet to be explored, which would highlight if unique information pertaining to muscle contraction and motion can be obtained from this real-time imaging modality. These new insights could inform how we assess muscle function and/or how we use this modality for assistive device control. Thus, our objective was to characterize the time synchronization of changes in five features of rectus femoris contraction extracted from ultrasound images during seated knee extension and flexion. A cross-correlation analysis was performed on data recorded by a handheld ultrasound system as able-bodied subjects completed seated trials of volitional knee extension and flexion. Changes in muscle thickness, angle between aponeuroses, and mean image echogenicity, a change in brightness of the grayscale image, preceded changes in our estimates of pennation angle and fascicle length. The leading nature of these features suggest they could be objective features for early detection of impending joint motion. Finally, multiple sonomyographic features provided unique temporal information associated with this volitional task.Clinical Relevance-This work evaluates the time relationship between five commonly reported features of skeletal muscle architecture during volitional motion, which can be used for targeted clinical assessments and intent detection.

Performance of Sonomyographic and Electromyographic Sensing for Continuous Estimation of Joint Torque During Ambulation on Multiple Terrains.

Advances in powered assistive device technology, including the ability to provide net mechanical power to multiple joints within a single device, have the potential to dramatically improve the mobility and restore independence to their users. However, these devices rely on the ability of their users to continuously control multiple powered lower-limb joints simultaneously. Success of such approaches rely on robust sensing of user intent and accurate mapping to device control parameters. Here, we compare two non-invasive sensing modalities: surface electromyography and sonomyography, (i.e., ultrasound imaging of skeletal muscle), as inputs to Gaussian process regression models trained to estimate hip, knee and ankle joint moments during varying forms of ambulation. Experiments were performed with ten non-disabled individuals instrumented with surface electromyography and sonomyography sensors while completing trials of level, incline (10°) and decline (10°) walking. Results suggest sonomyography of muscles on the anterior and posterior thigh can be used to estimate hip, knee and ankle joint moments more accurately than surface electromyography. Furthermore, these results can be achieved by training Gaussian process regression models in a task-independent manner; i.e., incorporating features of level and ramp walking within the same predictive framework. These findings support the integration of sonomyographic and electromyographic sensing within powered assistive devices to continuously control joint torque.

Ultrasound Sensing Can Improve Continuous Classification of Discrete Ambulation Modes Compared to Surface Electromyography.

Clinical translation of "intelligent" lower-limb assistive technologies relies on robust control interfaces capable of accurately detecting user intent. To date, mechanical sensors and surface electromyography (EMG) have been the primary sensing modalities used to classify ambulation. Ultrasound (US) imaging can be used to detect user-intent by characterizing structural changes of muscle. Our study evaluates wearable US imaging as a new sensing modality for continuous classification of five discrete ambulation modes: level, incline, decline, stair ascent, and stair descent ambulation, and benchmarks performance relative to EMG sensing. Ten able-bodied subjects were equipped with a wearable US scanner and eight unilateral EMG sensors. Time-intensity features were recorded from US images of three thigh muscles. Features from sliding windows of EMG signals were analyzed in two configurations: one including 5 EMG sensors on muscles around the thigh, and another with 3 additional sensors placed on the shank. Linear discriminate analysis was implemented to continuously classify these phase-dependent features of each sensing modality as one of five ambulation modes. US-based sensing statistically improved mean classification accuracy to 99.8% (99.5-100% CI) compared to 8-EMG sensors (85.8%; 84.0-87.6% CI) and 5-EMG sensors (75.3%; 74.5-76.1% CI). Further, separability analyses show the importance of superficial and deep US information for stair classification relative to other modes. These results are the first to demonstrate the ability of US-based sensing to classify discrete ambulation modes, highlighting the potential for improved assistive device control using less widespread, less superficial and higher resolution sensing of skeletal muscle.

Ultrasound Features of Skeletal Muscle Can Predict Kinematics of Upcoming Lower-Limb Motion.

Seamless integration of lower-limb assistive devices with the human body requires an intuitive human-machine interface, which would benefit from predicting the intent of individuals in advance of the upcoming motion. Ultrasound imaging was recently introduced as an intuitive sensing interface. The objective of the present study was to investigate the predictability of joint kinematics using ultrasound features of the rectus femoris muscle during a non-weight-bearing knee extension/flexion. Motion prediction accuracy was evaluated in 67 ms increments, up to 600 ms in time. Statistical analysis was used to evaluate the feasibility of motion prediction, and the linear mixed-effects model was used to determine a prediction time window where the joint angle prediction error is barely perceivable by the sample population, hence clinically reliable. Surprisingly, statistical tests revealed that the prediction accuracy of the joint angle was more sensitive to temporal shifts than the accuracy of the joint angular velocity prediction. Overall, predictability of the upcoming joint kinematics using ultrasound features of skeletal muscle was confirmed, and a time window for a statistically and clinically reliable prediction was found between 133 and 142 ms. A reliable prediction of user intent may provide the time needed for processing, control planning, and actuation of the assistive devices at critical points during ambulation, contributing to the intuitive behavior of lower-limb assistive devices.

Use of Sonomyographic Sensing to Estimate Knee Angular Velocity During Varying Modes of Ambulation.

Ultrasound (US) imaging of muscle has been introduced as a promising sensing modality for assistive device control. Ten able-bodied subjects completed level, incline and decline walking on a treadmill in a motion capture laboratory while wearing reflective markers on upper- and lower-body. A wearable US transducer was affixed to subjects' anterior thigh, and time-intensity features were extracted from transverse US images of the knee extensor muscles. These features were used to train and test Gaussian process regression models for continuous estimation of knee flexion/extension angular velocity. Four regression models were evaluated: (1) subject-dependent/task-specific, (2) subject-dependent/pooled-tasks, (3) subject-independent/task-specific, and (4) subject-independent/pooled-tasks. Subject-independent models were "tuned" with up to six strides of the test subject's data to boost performance. A two-factor analysis of variance test was used to assess the effect of each approach on root mean square error (RMSE) of estimated knee angular velocity (α=0.05). Statistical parametric mapping (SPM) was completed to compare actual vs. estimated knee angular velocity as a function of the gait cycle (α=0.05). For incline and level walking, the subject-dependent/pooled-tasks model resulted in the lowest error while the subject-dependent/task-specific model resulted in the lowest error for decline walk. Impressively, the two-factor test revealed no difference between task-specific and pooled-task models. Furthermore, despite capturing many important features of knee velocity across individuals there were, as expected, significant differences between subject-dependent and subject-independent models. Collectively, these results are promising for potential assistive device control with error rates <10% for all regression models that were tested.Clinical Relevance-This work is the first study to demonstrate the feasibility of using ultrasound-based sensing for estimation of knee angular velocity during multiple modes of ambulation.

The Effect of Neuromuscular Electrical Stimulation During Walking on Muscle Strength and Knee Pain in Obese Women With Knee Pain: A Randomized Controlled Trial.

OBJECTIVE: The aim of the study was to assess the effectiveness of a hybrid training system with walking that simultaneously applies electrical stimulation to the knee extensors/flexors during walking in obese women with knee pain. DESIGN: This is a randomized, single-blind (assessor), controlled trial. Twenty-eight obese women with knee pain were randomized to 12 weeks of biweekly walking with either hybrid training system with walking or with transcutaneous electrical nerve stimulation (control). Primary outcomes (maximum isokinetic knee extensor torque and maximum isokinetic knee flexor torque) and secondary outcomes (20-m walk time, chair-stand time, stair-climb time, knee pain, and knee-related quality life) were evaluated. Change-point regression analyses were used to model the interaction for the primary outcomes. Two-sample t tests were used on pre-post change scores in secondary outcomes. RESULTS: Knee extensor torque increased significantly more in the hybrid training system with walking group than the control group when baseline knee extensor torque was greater than 57.2 Nm (P = 0.0033). When baseline knee flexor torque was at 30 or 50 Nm, there was a trend toward greater increase in the hybrid training system with walking group than the control group (P = 0.0566, P = 0.0737, respectively). There were no significant differences between groups in secondary outcomes. CONCLUSIONS: These results suggest that hybrid training system with walking is effective for improving knee extensor torque in obese women with knee pain. However, the superiority of hybrid training system with walking may vary depending on baseline knee muscle strength.

The Relationship of Three-Dimensional Joint Space Width on Weight Bearing CT With Pain and Physical Function.

Limitations of plain radiographs may contribute to poor sensitivity in the detection of knee osteoarthritis and poor correlation with pain and physical function. 3D joint space width, measured from weight bearing CT images, may yield a more accurate correlation with patients' symptoms. We assessed the cross-sectional association between 3D joint space width and self-reported pain and physical function. 528 knees (57% women) were analyzed from Multicenter Osteoarthritis Study participants. An upright weight bearing CT scanner was used to acquire bilateral, weight-bearing fixed-flexion images of the knees. A 3D dataset was reconstructed from cone beam projections and joint space width was calculated across the joint surface. The percentages of the apposed medial tibiofemoral joint surface with joint space width <2.0mm and <2.5mm respectively were calculated. Pain and physical function were measured using Western Ontario and McMaster Universities Osteoarthritis Index. Participants who reported greater pain severity tended to have a greater joint area with joint space width <2.0mm (p=.07 for the highest vs. the lowest tertile). Participants who reported greater functional limitations had a greater joint area with joint space width <2.0mm (p=.02 for the highest vs. the lowest tertile). There appears to be an association between the medial tibiofemoral area with joint space width <2.0mm and pain and physical function. This article is protected by copyright. All rights reserved.

Gait Phase Identification During Level, Incline and Decline Ambulation Tasks Using Portable Sonomyographic Sensing.

Clinical viability of powered lower-limb assistive devices requires reliable and intuitive control strategies. Stance and swing are the main phases of the gait cycle across different locomotion tasks. Hence, a reliable method to accurately identify these phases can decrease sensing complexity and assist in enabling high-level control of assistive devices. Ultrasound (US) imaging has recently been introduced as a new sensing modality that may provide a solution for intuitive device control. US images of the rectus femoris and vastus intermedius muscles were collected in humans during level, incline, and decline ambulation tasks. Five low-level static (i.e. time-independent) features of US images were measured with respect to a reference image, including correlation coefficient, sum of absolute differences, structural similarity index, sum of squared differences, and image echogenicity. Time-derivatives of the static features were also calculated as temporal features. Support vector machine classifiers were trained using these static features to identify the gait phase both dependent and independent of the ambulation tasks. The results indicate an accuracy of 88.3% in identifying the gait phases for task-independent classifiers when trained using only the static features. Performance of the classifiers improved significantly to 92.8% after using the temporal features (p $\lt0.01)$. The algorithm was efficient and the average processing speed was faster than 100 Hz. This study is the first demonstration on use of US imaging to provide continuous estimates of ambulation phase, and on multiple surfaces. These findings suggest task-independent approaches may reliably identify the main phases of the gait cycle. Advancements in this area of study may provide simpler intuitive strategies for high-level assistive device control and increase their clinical relevance.

Evaluation of the Combined Application of Neuromuscular Electrical Stimulation and Volitional Contractions on Thigh Muscle Strength, Knee Pain, and Physical Performance in Women at Risk for Knee Osteoarthritis: A Randomized Controlled Trial.

BACKGROUND: Knee osteoarthritis (OA) is a leading cause of disability that is associated with quadriceps weakness. However, strengthening in people with or with risk factors for knee OA can be poorly tolerated. OBJECTIVE: To assess the efficacy of a 12-week low-load exercise program, using a hybrid training system (HTS) that uses the combination of neuromuscular electrical stimulation and volitional contractions, for improving thigh muscle strength, knee pain relief, and physical performance in women with or with risk factors for knee OA. DESIGN: Randomized, single-blinded, controlled trial. SETTING: Exercise training laboratory. PARTICIPANTS: Forty-two women 44-85 years old with risk factors for knee OA. INTERVENTIONS: Participants randomized to 12 weeks of biweekly low-load resistance training with the HTS or on an isokinetic dynamometer (control). OUTCOMES: Maximum isokinetic knee extensor torque. Secondary measures included maximum isokinetic knee flexor torque, knee pain (Knee Injury and Osteoarthritis Outcome Score), and timed 20-m walk and chair stand tests. RESULTS: The HTS and control treatments resulted in muscle strengthening, decreased knee pain, and improved physical performance. HTS group quadriceps and hamstring strength increased by 0.06 ± 0.04 Nm/kg (P > .05) and 0.05 ± 0.02 Nm/kg (P = .02), respectively. Control group quadriceps and hamstring strength increased by 0.03 ± 0.04 Nm/kg (P > .05) and 0.06 ± 0.02 Nm/kg (P = .009), respectively. Knee pain decreased by 11.9 ± 11.5 points (P < .001) for the HTS group and 14.1 ± 15.4 points (P = .001) for the control group. The 20-m walk time decreased by 1.60 ± 2.04 seconds (P = .005) and 0.95 ± 1.2 seconds (P = .004), and chair stand time decreased by 4.8 ± 10.0 seconds (P > .05) and 1.9 ± 4.7 seconds (P > .05) in the HTS and control groups, respectively. These results did not differ statistically between the HTS and control groups. CONCLUSIONS: These results suggest the HTS is effective for alleviating pain and improving physical performance in women with risk factors for knee OA. However, the HTS does not appear to be superior to low-load resistance training for improving muscle strength, pain relief, or physical function. CLINICAL TRIAL REGISTRATION NUMBER: NCT02802878. LEVEL OF EVIDENCE: I.

The Effect of Arch Drop on Tibial Rotation and Tibiofemoral Contact Stress in Postpartum Women.

BACKGROUND: Women are at greater risk for knee osteoarthritis and numerous other lower limb musculoskeletal disorders. Arch drop during pregnancy and the resultant excessive pronation of the feet may alter loading patterns and contribute to the greater prevalence of knee osteoarthritis in women. OBJECTIVE: To determine the effect of arch drop on tibial rotation and tibiofemoral contact stress. DESIGN: Interventional study with internal control. SETTING: Biomechanics laboratory. PARTICIPANTS: Eleven postpartum women (age 33.4 ± 5.3 years, body mass 76.1 ± 13.5 kg) who had lost arch height with pregnancy in a previous study. METHODS: Subjects underwent standing computed tomography (SCT) with their knees in a 20° fixed-flexed position with and without semirigid arch supports to reconstitute prepregnancy arch height. Magnetic resonance imaging of the knee was acquired at a flexion angle equivalent to that of SCT. Bone and cartilage were manually segmented on the magnetic resonance images and segmented surfaces were registered to the 3-dimensional SCT image sets for the arch-supported and -unsupported conditions. These models were used to measure changes in tibial rotation, as well as to estimate contact stress in the medial and lateral tibiofemoral compartments, using computational methods. MAIN OUTCOME MEASURES: Change in tibial rotation and tibiofemoral contact stress with arch drop. RESULTS: Arch drop resulted in a mean tibial internal rotation of 0.75 ± 1.33° (P = .02). Changes in mean or peak contact stress were not detected. CONCLUSIONS: Arch drop causes internal tibial rotation, resulting in a shift in the tibiofemoral articulation. An associated increase in contact stress was not detected. Internal rotation of the tibia increases stress on the anterior cruciate ligament and menisci, potentially explaining the greater prevalence of knee disorders in postpartum women. LEVEL OF EVIDENCE: NA.