Propulsive joint powers track with sensor-derived angular velocity: A potential tool for lab-less gait retraining

Efficacy of a Single-Bout of Auditory Feedback Training on Gait Performance and Kinematics in Healthy Young Adults

This study investigated the immediate effects of auditory feedback training on gait performance and kinematics in 19 healthy young adults, focusing on bilateral changes, despite unilateral training. Baseline and post-training kinematic measurements, as well as the feedback training were performed on a treadmill with a constant velocity. Significant improvements were seen in step length (trained: 590.7 mm to 611.1 mm, 95%CI [7.609, 24.373]; untrained: 591.1 mm to 628.7 mm, 95%CI [10.698, 30.835]), toe clearance (trained: 13.9 mm to 16.5 mm, 95%CI [1.284, 3.503]; untrained: 11.8 mm to 13.7 mm, 95%CI [1.763, 3.612]), ankle dorsiflexion angle at terminal stance (trained: 8.3 deg to 10.5 deg, 95%CI [1.092, 3.319]; untrained: 9.2 deg to 12.0 deg, 95%CI [1.676, 3.573]), hip flexion angular velocity, (trained: -126.5 deg/s to -131.0 deg/s, 95%CI [-9.054, -2.623]; untrained: -130.2 deg/s to -135.3 deg/s, 95%CI [-10.536, -1.675]), ankle angular velocity at terminal stance (trained: -344.7 deg/s to -359.1 deg/s, 95%CI [-47.540, -14.924]; untrained: -340.3 deg/s to -376.9 deg/s, 95%CI [-37.280, -13.166s]), and gastrocnemius EMG activity (trained: 0.60 to 0.66, 95%CI [0.014, 0.258]; untrained: 0.55 to 0.65, 95%CI [0.049, 0.214]). These findings demonstrate the efficacy of auditory feedback training in enhancing key gait parameters, highlighting the bilateral benefits from unilateral training.

Assessment of Foot Strike Angle and Forward Propulsion with Wearable Sensors in People with Stroke

Effective retraining of foot elevation and forward propulsion is a critical aspect of gait rehabilitation therapy after stroke, but valuable feedback to enhance these functions is often absent during home-based training. To enable feedback at home, this study assesses the validity of an inertial measurement unit (IMU) to measure the foot strike angle (FSA), and explores eight different kinematic parameters as potential indicators for forward propulsion. Twelve people with stroke performed walking trials while equipped with five IMUs and markers for optical motion analysis (the gold standard). The validity of the IMU-based FSA was assessed via Bland-Altman analysis, ICC, and the repeatability coefficient. Eight different kinematic parameters were compared to the forward propulsion via Pearson correlation. Analyses were performed on a stride-by-stride level and within-subject level. On a stride-by-stride level, the mean difference between the IMU-based FSA and OMCS-based FSA was 1.4 (95% confidence: -3.0; 5.9) degrees, with ICC = 0.97, and a repeatability coefficient of 5.3 degrees. The mean difference for the within-subject analysis was 1.5 (95% confidence: -1.0; 3.9) degrees, with a mean repeatability coefficient of 3.1 (SD: 2.0) degrees. Pearson's r value for all the studied parameters with forward propulsion were below 0.75 for the within-subject analysis, while on a stride-by-stride level the foot angle upon terminal contact and maximum foot angular velocity could be indicative for the peak forward propulsion. In conclusion, the FSA can accurately be assessed with an IMU on the foot in people with stroke during regular walking. However, no suitable kinematic indicator for forward propulsion was identified based on foot and shank movement that could be used for feedback in people with stroke.

Monitoring physical activity using wearable technology in people with Achilles tendinopathy undergoing physiotherapy treatment: A feasibility prospective cohort study

OBJECTIVES

Physical activity modification is an important part of the management of Achilles tendinopathy. However, to our knowledge, there is a lack of evidence on objective physical activity assessment in Achilles tendinopathy. The purpose of this study is to (1) assess feasibility of using an inertial measurement unit (IMU) to monitor physical activity and IMU-derived biomechanical measures over 12-week treatment course by a physiotherapist; (2) conduct a preliminary analysis of changes in physical activity over 12-weeks.

DESIGN

A feasibility prospective cohort study SETTING: A community setting.

PARTICIPANTS

People with Achilles tendinopathy who had recently commenced (≤2 sessions), or were about to commence, treatment with a physiotherapist MAIN OUTCOME MEASURES: Participants wore a shank-mounted IMU on the affected side for one week at baseline, 6-, and 12-week follow-ups. The outcomes were pain/symptom severity, IMU-derived physical activity and biomechanical measures (stride rate, peak shank angular velocity, and peak shank acceleration).

RESULTS

Thirty participants were recruited. There was a high retention rate (97%), response rate (97%), and IMU wear compliance at each timepoint (>93%). For pain/symptom severity, a significant time effect was observed between baseline and 12-week follow-up. Physical activity and IMU-derived biomechanical measures did not change over 12 weeks. Physical activity decreased at the 6-week follow-up but only returned to the baseline level at 12-week follow-up.

CONCLUSIONS

A larger-scale cohort study assessing clinical outcomes and physical activity appears feasible. Preliminary data indicate that physical activity may not change significantly over 12-weeks in people undergoing physiotherapy management for Achilles tendinopathy. CONTRIBUTION OF THE PAPER.

Challenges and advances in the use of wearable sensors for lower extremity biomechanics

The use of wearable sensors for the collection of lower extremity biomechanical data is increasing in popularity, in part due to the ease of collecting data and the ability to capture movement outside of traditional biomechanics laboratories. Consequently, an increasing number of researchers are facing the challenges that come with utilizing the data captured by wearable sensors. These challenges include identifying/calculating meaningful measures from unfamiliar data types (measures of acceleration and angular velocity instead of positions and joint angles), defining sensor-to-segment alignments for calculating traditional biomechanics metrics, using reduced sensor sets and machine learning to predict unmeasured signals, making decisions about when and how to make algorithms freely available, and developing or replicating methods to perform basic processing tasks such as recognizing activities of interest or identifying gait events. In this perspective article, we present our own approaches to common challenges in lower extremity biomechanics research using wearable sensors and share our perspectives on approaching several of these challenges. We present these perspectives with examples that come mostly from gait research, but many of the concepts also apply to other contexts where researchers may use wearable sensors. Our goal is to introduce common challenges to new users of wearable sensors, and to promote dialogue amongst experienced users towards best practices.

Prediction of lower limb kinematics from vision-based system using deep learning approaches

The joint angular velocity during daily life exercises is an important clinical outcome for injury risk index, rehabilitation progress monitoring and athlete's performance evaluation. Recently, wearable sensors have been widely used to monitor lower limb kinematics. However, these sensors are difficult and inconvenient to use in daily life. To mitigate these limitations, this study proposes a vision-based system for estimating lower limb joint kinematics using a deep convolution neural network with bi-directional long-short term memory and gated recurrent unit network. The normalized correlation coefficient, and the mean absolute error were computed between the ground truth obtained from the optical motion capture system and estimated joint angular velocities using proposed models. The estimated results show a highest correlation 0.93 in squat and 0.92 in walking on treadmill action. Furthermore, independent model for each joint angular velocity at the hip, knee, and ankle were analyzed and compared. Among the three joint angular velocities, knee joint has a best estimated accuracy (0.96 in squat and 0.96 in walking on the treadmill). The proposed models show higher estimation accuracy under both the lateral and the frontal view regardless of the camera positions and angles. This study proves the applicability of using sensor free vision-based system to monitor the lower limb kinematics during home workouts for healthcare and rehabilitation.

Evaluating daily physical activity and biomechanical measures using wearable technology in people with Achilles tendinopathy: A descriptive exploratory study

BACKGROUND

Load management is considered an important factor for prevention and treatment of Achilles tendinopathy. However, little attention has been given to monitoring daily load objectively in this population.

OBJECTIVES

We aimed to explore patterns in proxies of daily load derived from a six-axis inertial measurement unit (IMU) over a one-week period and the concordance between day-to-day fluctuation in pain intensity and IMU measures.

DESIGN

Descriptive exploratory study.

METHOD

Ten participants with Achilles tendinopathy (age: 53.00 ± 12.37) wore an IMU on the affected ankle for one week. Participants were contacted via text message three times daily to rate their worst pain intensity. Physical activity and biomechanical measures derived from the IMU signals including daily number of steps, peak stride rate, peak shank acceleration, and peak shank angular velocity were calculated.

RESULTS

The relationship between weekly worst pain and physical activity levels appeared modest; with increased steps not seeming to be linked to increased or reduced pain levels. According to the daily pain and daily IMU measures, a concordant pattern was evident in younger, highly active participants. However, in the middle-aged/older less active participants, there was either a fluctuation in pain intensity without fluctuation in the IMU measures, or a stable pattern of both pain and IMU measures.

CONCLUSIONS

Our exploratory study results suggest that continuous monitoring of proxies of daily load measures in parallel with pain may provide information about load management strategies in people with Achilles tendinopathy. Monitoring of these proxies may ultimately have a role in improving Achilles tendinopathy management.