Three-dimensional (3D) knee angle measurement is one of the key measures in human gait analysis. Inertial sensor capable of measuring joint motion under unconstrained conditions is a practical tool for clinical evaluation and rehabilitation. An inertial measurement unit (IMU) consisting of accelerometer and gyroscope allows orientation measurement in 3D with an additional sensor (i.e., magnetometer). However, ferromagnetic interference negatively affects the performance of magnetometer and thus reduces measurement accuracy. In this study, a technique based on nonlinear autoregressive neural network with exogenous inputs (NARX) is presented to measure 3D segmental orientation during gait without the use of magnetometer. With IMUs attached to the thigh and shank, 3D knee angles in long-distance treadmill walking were computed and validated against an optical motion analysis system as the gold standard. Pseudo-integrator (PI) was also compared to the reference system for benchmarking. The learning capability of NARX was further assessed with the comparison of complementary filter (CF) to the reference system. The proposed NARX model was shown to outperform PI with biases between-3.5°and-0.2°, and root mean square errors between 4.5°and 2.5°. Results demonstrated the capability of NARX in providing accurate estimates of 3D knee joint angle while avoiding interference as encountered in systems incorporating magnetometer, suggesting that NARX is feasible to computing long-term ambulatory measurements of body segment orientation and 3D joint angles. INDEX TERMS 3D knee angle, gait analysis, NARX network, pseudo-integration, segmental orientation.

A systematic review of the mechanical design of powered ankle-foot prostheses developed from 2000 to 2019 was conducted through database and manual searches. A total of 10 English and two Chinese databases were searched using the same keywords. Moreover, information on commercialized prostheses was collected through a manual search. A total of 8,729 publications were obtained from the database search, and 83 supplementary publications and 49 online product introductions were accumulated through the manual search. A total of 91 powered ankle-foot prostheses were extracted from 159 publications and online information after exclusion. The mechanical design characteristics of the prostheses were described briefly and compared after they were categorized into 11 subclassifications. This review revealed that a considerable number of powered ankle-foot prostheses were developed in the last 20 years. The development of such prostheses was characterized by alternative modes, that is, from pneumatic or hydraulic drivers to motorized drivers and from rigid transmissions to elastic actuators. This review contributes to the comprehensive understanding of current designs, which can benefit the combination of the advantages of and redundancy avoidance in future powered ankle-food protheses.

3D printing is the most suitable method to manufacture the frame parts of powered ankle-foot prostheses but the compressive strength of the 3D-printed part needs to be ensured. According to the compression test standard ASTM D695, the effect of infill pattern and density, which is transferred to the mass of the standard specimen, on the compressive strength is investigated with a carbon fiber-reinforced nylon material. With the same infill pattern, specimens with more mass have a higher compressive strength. With the same mass, specimens with triangular fill have a higher compressive strength than those with rectangular and gyroid fills. Compared with specimens with a solid fill, specimens with a triangular fill can also provide more compressive strength in a unit mass. According to the results of standard specimens, following the requirement of strength and lightweight, 41% triangular fill is selected to manufacture the supporting part of a powered ankle-foot prosthesis. Under a compressive load of 1225 N, the strain of the assembly of the standard adaptor and the 3D-printed part is 1.32 ± 0.04%, which can meet the requirement of the design. This study can provide evidence for other 3D-printed applications with the requirement of compressive strength.

This article presents a novel sensorless control system of assistive robotic ankle-foot prosthesis, two estimation algorithms were developed and an analogy between them has been made. The system actuator's motor is a permanent magnet synchronous motor, unlike other powered ankle-foot, where the brushless DC motor and DC motor were used. Utilizing the permanent magnet synchronous motor will reduce the torque ripples and increase system ability to be overloaded compared to systems which utilize the brushless DC motor. Moreover, the ability of the machine to operate in all speed range makes this machine more suitable for the application. Both estimation algorithms are built using C-code and assessed in MATLAB Simulink. The estimation algorithms are used to provide motor and powered ankle-foot's angular speed and position. Two-level control system is used to evaluate the estimation algorithms; the control system role is to mimic biological ankle-foot performance during normal ground level walking speed. Based on the result of this article the unscented Kalman filter (UKF) is applicable for the application, as a result of the observer ability to estimate the motor load and angular position. On the other hand, extended Kalman filter (EKF) accuracy is affected by the load applied to the motor. Furthermore, the angular position is evaluated by integration of the angular speed which means integration of angular speed estimation error.

Planar spiral spring is important for the dimensional miniaturisation of motor-based elastic actuators. However, when the stiffness calculation of the spring arm is based on simple beam bending theory, the results possess substantial errors compared with the stiffness obtained from finite-element analysis (FEA). It deems that the errors arise from the spiral length term in the calculation formula. Two Gaussian process regression models are trained to amend this term in the stiffness calculation of spring arm and complete spring. For the former, 216 spring arms’ data sets, including different spiral radiuses, pitches, wrap angles and the stiffness from FEA, are employed for training. The latter engages 180 double-arm springs’ data sets, including widths instead of wrap angles. The simulation of five spring arms and five planar spiral springs with arbitrary dimensional parameters verifies that the absolute values of errors between the predicted stiffness and the stiffness from FEA are reduced to be less than 0.5% and 2.8%, respectively. A planar spiral spring for a powered ankle–foot prosthesis is designed and manufactured to verify further, of which the predicted value possesses a 3.25% error compared with the measured stiffness. Therefore, the amendment based on the prediction of trained models is available.

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