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1. Closing the Wearable Gap—Part IV: 3D Motion Capture Cameras Versus Soft Robotic Sensors Comparison of Gait Movement Assessment

   https://doi.org/10.3390/electronics8121382  

   Saucier, David; Davarzani, Samaneh; Turner, Alana; Luczak, Tony; Nguyen, Phuoc; Carroll, Will; Burch V, Reuben F.; Ball, John E.; Smith, Brian K.; Chander, Harish; et al (December 2019, Electronics)

   The purpose of this study was to use 3D motion capture and stretchable soft robotic sensors (SRS) to collect foot-ankle movement on participants performing walking gait cycles on flat and sloped surfaces. The primary aim was to assess differences between 3D motion capture and a new SRS-based wearable solution. Given the complex nature of using a linear solution to accurately quantify the movement of triaxial joints during a dynamic gait movement, 20 participants performing multiple walking trials were measured. The participant gait data was then upscaled (for the SRS), time-aligned (based on right heel strikes), and smoothed using filtering methods. A multivariate linear model was developed to assess goodness-of-fit based on mean absolute error (MAE; 1.54), root mean square error (RMSE; 1.96), and absolute R2 (R2; 0.854). Two and three SRS combinations were evaluated to determine if similar fit scores could be achieved using fewer sensors. Inversion (based on MAE and RMSE) and plantar flexion (based on R2) sensor removal provided second-best fit scores. Given that the scores indicate a high level of fit, with further development, an SRS-based wearable solution has the potential to measure motion during gait- based tasks with the accuracy of a 3D motion capture system. 

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2. Closing the Wearable Gap—Part II: Sensor Orientation and Placement for Foot and Ankle Joint Kinematic Measurements

   https://doi.org/10.3390/s19163509  

   Saucier, David; Luczak, Tony; Nguyen, Phuoc; Davarzani, Samaneh; Peranich, Preston; Ball, John E.; Burch, Reuben F.; Smith, Brian K.; Chander, Harish; Knight, Adam; et al (August 2019, Sensors)

   The linearity of soft robotic sensors (SRS) was recently validated for movement angle assessment using a rigid body structure that accurately depicted critical movements of the foot–ankle complex. The purpose of this study was to continue the validation of SRS for joint angle movement capture on 10 participants (five male and five female) performing ankle movements in a non-weight bearing, high-seated, sitting position. The four basic ankle movements—plantar flexion (PF), dorsiflexion (DF), inversion (INV), and eversion (EVR)—were assessed individually in order to select good placement and orientation configurations (POCs) for four SRS positioned to capture each movement type. PF, INV, and EVR each had three POCs identified based on bony landmarks of the foot and ankle while the DF location was only tested for one POC. Each participant wore a specialized compression sock where the SRS could be consistently tested from all POCs for each participant. The movement data collected from each sensor was then compared against 3D motion capture data. R-squared and root-mean-squared error averages were used to assess relative and absolute measures of fit to motion capture output. Participant robustness, opposing movements, and gender were also used to identify good SRS POC placement for foot–ankle movement capture. 

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3. Closing the Wearable Gap—Part VI: Human Gait Recognition Using Deep Learning Methodologies

   https://doi.org/10.3390/electronics9050796  

   Davarzani, Samaneh; Saucier, David; Peranich, Preston; Carroll, Will; Turner, Alana; Parker, Erin; Middleton, Carver; Nguyen, Phuoc; Robertson, Preston; Smith, Brian; et al (May 2020, Electronics)

   A novel wearable solution using soft robotic sensors (SRS) has been investigated to model foot-ankle kinematics during gait cycles. The capacitance of SRS related to foot-ankle basic movements was quantified during the gait movements of 20 participants on a flat surface as well as a cross-sloped surface. In order to evaluate the power of SRS in modeling foot-ankle kinematics, three-dimensional (3D) motion capture data was also collected for analyzing gait movement. Three different approaches were employed to quantify the relationship between the SRS and the 3D motion capture system, including multivariable linear regression, an artificial neural network (ANN), and a time-series long short-term memory (LSTM) network. Models were compared based on the root mean squared error (RMSE) of the prediction of the joint angle of the foot in the sagittal and frontal plane, collected from the motion capture system. There was not a significant difference between the error rates of the three different models. The ANN resulted in an average RMSE of 3.63, being slightly more successful in comparison to the average RMSE values of 3.94 and 3.98 resulting from multivariable linear regression and LSTM, respectively. The low error rate of the models revealed the high performance of SRS in capturing foot-ankle kinematics during the human gait cycle. 

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4. Stair Ascent Phase-Variable Control of a Powered Knee-Ankle Prosthesis

   Cortino, Ross; Bolivar, Edgar; Best, Thomas K.; Gregg, Robert D. (January 2022, IEEE International Conference on Robotics and Automation)

   Passive prostheses cannot provide the net positive work required at the knee and ankle for step-over stair ascent. Powered prostheses can provide this net positive work, but user synchronization of joint motion and power input are critical to enabling natural stair ascent gaits. In this work, we build on previous phase variable-based control methods for walking and propose a stair ascent controller driven by the motion of the user's residual thigh. We use reference kinematics from an able-bodied dataset to produce knee and ankle joint trajectories parameterized by gait phase. We redefine the gait cycle to begin at the point of maximum hip flexion instead of heel strike to improve the phase estimate. Able-bodied bypass adapter experiments demonstrate that the phase variable controller replicates normative able-bodied kinematic trajectories with a root mean squared error of 12.66 deg and 2.64 deg for the knee and ankle, respectively. The knee and ankle joints provided on average 0.387J/kg and 0.212J/kg per stride, compared to the normative averages of 0.335J/kg and 0.207J/kg, respectively. Thus, this controller allows powered knee-ankle prostheses to perform net positive mechanical work to assist stair ascent. 

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5. Functional Evaluation of a Personalized Orthosis for Knee Osteoarthritis: A Motion Capture Analysis

   https://doi.org/10.1115/1.4051626  

   Huber, Martin; Eschbach, Matthew; Kazerounian, Kazem; Ilies, Horea (December 2021, Journal of Medical Devices)

   null (Ed.)

   Abstract Orthotic treatments for knee osteoarthritis (OA) typically rely on simple mechanisms such as three-point bending straps and single-pin hinges. These commonly prescribed braces cannot treat bicompartmental knee OA, do not consider the muscle weakness that typically accompanies the condition, and employ hinges that restrict the knee's natural biomechanics. Utilizing a novel, personalized joint mechanism in conjunction with magnetorheological dampers, we have developed and evaluated a brace which attempts to address these shortcomings. This process has respected three principal design goals: reducing the load experienced across the entire knee joint, generating a supportive moment to aid the thigh muscles in shock absorption, and interfering minimally with gait kinematics. Two healthy volunteers were chosen to test the system's basic functionality through gait analysis in a motion capture laboratory. Combining the collected kinematic and force-plate data with data taken from sensors onboard the brace, we integrated the brace and leg system into a single inverse dynamics analysis, from which we were able to evaluate the effect of the brace design on the subjects' knee loads and moments. Of the three design goals: a reduction in knee contact forces was demonstrated; increased shock absorption was observed, but not to statistical significance; and natural gait was largely preserved. Taken in total, the outcome of this study supports additional investigation into the system's clinical effectiveness, and suggests that further refinement of the techniques presented in this paper could open the doors to more effective OA treatment through patient specific braces. 

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