Robotic Transtibial Prosthesis Research Articles

Air microfluidics-enabled soft robotic transtibial prosthesis socket liner toward dynamic management of residual limb contact pressure and volume fluctuation.

Residual limb volume fluctuation and the resulting contact pressures are some of the key factors leading to skin ulcerations, suboptimal prosthetic functioning, pain, and diminishing quality of life of transtibial amputees. Self-management of socket fit is complicated by peripheral neuropathy, reducing the perception of pressure and pain in the residual limb. We introduce a novel proof-of-concept for a transtibial prosthetic socket liner with the potential to dynamically adjust the fit between the limb and socket. The core of the technology is a small air microfluidic chip (10 cm3 and 10 g) with 10 on-chip valves that enable sequential pressurizing of 10 actuators in custom sizes to match the pressures required by the residual limb's unique anatomy. The microfluidic chip largely reduced the number of electromechanical solenoid valves needed for sequential control of 10 actuators (2 instead of 10 valves), resulting in the reduction of the required power, size, mass, and cost of the control box toward an affordable and wearable prosthetic socket. Proof-of-concept testing demonstrated that the applied pressures can be varied in the desired sequence and to redistribute pressure. Future work will focus on integrating the system with biofidelic prosthetic sockets and residual limb models to investigate the ability to redistribute pressure away from pressure-sensitive regions (e.g., fibular head) to pressure tolerant areas. Overall, the dynamic prosthesis socket liner is very encouraging for creating a dynamic socket fit system that can be seamlessly integrated with existing socket fabrication methods for managing residual limb volume fluctuations and contact pressure.

Adaptive estimation of continuous gait phase based on capacitive sensors.

Continuous gait phase plays an important role in robotic prosthesis control. In this paper, we have conducted the offline adaptive estimation (at different speeds and on different ramps) of continuous gait phase of robotic transtibial prosthesis based on the adaptive oscillators. We have used the capacitive sensing method to record the deformation of the muscles. Two transtibial amputees joined in this study. Based on the strain signals of the prosthetic foot and the capacitive signals of the residual limb, the maximum and minimum of estimation errors are 0.80rad and 0.054rad, respectively, and their corresponding ratios in one gait cycle are 1.27% and 0.86%, respectively. This paper proposes an effective method to estimate the continuous gait phase based on the capacitive signals of the residual muscles, which provides a basis for the continuous control of robotic transtibial prosthesis.

On-board Training Strategy for IMU-Based Real-Time Locomotion Recognition of Transtibial Amputees With Robotic Prostheses.

The paper puts forward an on-board strategy for a training model and develops a real-time human locomotion mode recognition study based on a trained model utilizing two inertial measurement units (IMUs) of robotic transtibial prosthesis. Three transtibial amputees were recruited as subjects in this study to finish five locomotion modes (level ground walking, stair ascending, stair descending, ramp ascending, and ramp descending) with robotic prostheses. An interaction interface was designed to collect sensors' data and instruct to train model and recognition. In this study, the analysis of variance ratio (no more than 0.05) reflects the good repeatability of gait. The on-board training time for SVM (Support Vector Machines), QDA (Quadratic Discriminant Analysis), and LDA (Linear discriminant analysis) are 89, 25, and 10 s based on a 10,000 × 80 training data set, respectively. It costs about 13.4, 5.36, and 0.067 ms for SVM, QDA, and LDA for each recognition process. Taking the recognition accuracy of some previous studies and time consumption into consideration, we choose QDA for real-time recognition study. The real-time recognition accuracies are 97.19 ± 0.36% based on QDA, and we can achieve more than 95% recognition accuracy for each locomotion mode. The receiver operating characteristic also shows the good quality of QDA classifiers. This study provides a preliminary interaction design for human–machine prosthetics in future clinical application. This study just adopts two IMUs not multi-type sensors fusion to improve the integration and wearing convenience, and it maintains comparable recognition accuracy with multi-type sensors fusion at the same time.

Maximum Dorsiflexion Detection Based on an On-Board Adaptive Algorithm for Transtibial Amputees With Robotic Prostheses

Maximum dorsiflexion (MDF) is an important gait event corresponding to the maximum ankle dorsiflexion angle in each gait cycle. MDF timing plays an important role in the control of robotic prosthesis. This article puts forward an on-board adaptive algorithm to detect MDF timing of robotic transtibial prosthesis in different walking conditions (at different speeds and on different ramps) and for different users. Based on the adaptive algorithm, we can get a time-variant detection model. The framework of the adaptive algorithm is composed of: 1) training data collecting and labeling; 2) model training and real-time detection; and 3) model updating according to the detection results. Based on the adaptive algorithm, we conducted speed and ramp experiments to detect MDF timings at slow, normal, and fast speeds, and on ramps with different inclination angles (10°, 5°, 0°, -5°, and -10°). Three transtibial amputee participated in the experiments. The model training/updating time ranges from 3.6 to 4.1 s and the detection time ranges from 0.95 to 1.17 ms for different speeds and ramps. In real-time detection, there is false detection (1.67%) at normal walking speed. In addition, all MDF timings are detected correctly (accuracy: 100%) based on the adaptive algorithm. The mean detection delays are 7.23, 18.27, and 7.5 ms corresponding to slow, normal and fast speeds and 10.60, 10.30, 18.27, 10.27, and 15.63 ms for ramps of different inclination angles (10°, 5°, 0°, -5°, and -10°). Compared with the proposed adaptive algorithm, both the nonadaptive and adaptive threshold decision methods cause more false detections. The results show that the proposed approach for MDF timing detection has adaptations to different walking conditions (speeds and ramps) and prosthesis users, which indicates that the adaptive algorithm is effective and shows the potential in robotic prosthesis control in the future. Note to Practitioners-This article proposes an on-board adaptive algorithm to detect the maximum dorsiflexion (MDF) timing based on inertial measurement unit (IMU) and ankle angle sensor for robotic transtibial prosthesis users in each gait cycle. IMU and angle sensor are integrated in the prosthesis, and the adaptive algorithm is embedded in the control circuit of prosthesis. The adaptive algorithm can realize the model updating continuously for real-time MDF timing detection with collected and labeled training data. The proposed adaptive algorithm shows satisfactory adaptation for MDF timing detection in different walking speed and ramp conditions. In addition, the adaptive algorithm also shows some generalizations for prosthesis users, which are useful to improve prosthesis control.

Locomotion Mode Recognition With Robotic Transtibial Prosthesis in Inter-Session and Inter-Day Applications

Locomotion mode recognition across multiple sessions and days is an indispensable step towards the practical use of the robotic transtibial prosthesis. In this study, we proposed an adaptive recognition strategy to against the time-varying features of on-prosthesis mechanical signals in inter-session and inter-day recognition tasks. The strategy was designed with an automatic training algorithm which could update the classifiers with the data of the most recent completed gait cycles to seize the changes of the features brought by external disturbances. After implementation, we measured multiple experimental sessions on six transtibial amputees with intervals from a few hours (inter-session experiment) to several months (108 days at most in inter-day experiment). In each session, they performed five locomotion modes and eight locomotion transitions using the robotic prosthesis. Between each two experimental sessions, the subjects were required to doff the robotic prosthesis (including the socket). The proposed adaptive recognition algorithm significantly improved recognition accuracies in both experiments. In inter-session experiment, the proposed method increased the recognition accuracy from 89.3% to 92.8% than previous non-adaptive recognition method. In inter-day experiments, it increased the recognition accuracy from 60% to 88.8%. If taking three modes (level walking, stair ascending/descending) and four locomotion transitions into calculation, the recognizer produced an accuracy up to 96.6% (swing phase) for static mode and an accuracy of 96.9% for locomotion transitions on inter-day tasks without manual intervenes. Compared with state-of-the-art, our study extends the ability of the robotic transtibial prosthesis in locomotion mode recognition across multiple sessions and days. Future efforts are worth being paid in this direction to get more promising results.

Development and Evaluation of a Powered Artificial Gastrocnemius for Transtibial Amputee Gait

Existing robotic transtibial prostheses provide only ankle joint actuation and do not restore biarticular function of the gastrocnemius muscle. This paper presents the first powered biarticular transtibial prosthesis, which is a combination of a commercial powered ankle-foot prosthesis and a motorized robotic knee orthosis. The orthosis is controlled to emulate the human gastrocnemius based on neuromuscular models of matched nonamputees. Together with the ankle-foot prosthesis, the devices provide biarticular actuation. We evaluate differences between this biarticular condition and a monoarticular condition with the orthosis behaving as a free-joint. Six participants with transtibial amputation walk with the prosthesis on a treadmill while motion, force, and metabolic data are collected and analyzed for differences between conditions. The biarticular prosthesis reduces affected-side biological knee flexion moment impulse and hip positive work during late-stance knee flexion, compared to the monoarticular condition. The data do not support our hypothesis that metabolism decreases for all participants, but some participants demonstrate large metabolic reductions with the biarticular condition. These preliminary results suggest that a powered artificial gastrocnemius may be capable of providing large metabolic reductions compared to a monoarticular prosthesis, but further study is warranted to determine an appropriate controller for achieving more consistent metabolic benefits.

Energy-Efficient Braking Torque Control of Robotic Transtibial Prosthesis

The ankle joint usually rotates passively during early and middle stance due to the locomotion of human body. Based on this passive dynamics of human locomotion, we develop an energy-efficient braking torque controller for a robotic transtibial prosthesis. The controller first generates motor current/torque from human locomotion instead of the battery energy, and then controls the current/torque with alternating current sensing and voltage-controlled-resistor. On the basis of the low-level motor torque controller, we then propose the impedance model that determines the desired joint torque according to the joint angle and joint velocity, the prosthesis model that converts the desired ankle joint torque to desired motor torque, and the friction model that estimates the friction torque and compensates the joint torque. Step response and frequency response show that the low-level controller can reach the desired torque value within 0.07 s, and has a $-$ 3 $\text{dB}$ bandwidth of 25.2 $\text{Hz}$ . Experiments of level-ground treadmill walking with three amputees show that the prosthesis with the proposed controller can effectively mimic the normal ankle performance and bring the amputees a natural gait pattern with low power consumption.

Combining Vibrotactile Feedback with Volitional Myoelectric Control for Robotic Transtibial Prostheses.

In recent years, the development of myoelectric control for robotic lower-limb prostheses makes it possible for amputee users to volitionally control prosthetic joints. However, the human-centered control loop is not closed due to the lack of sufficient feedback of prosthetic joint movement, and it may result in poor control performance. In this research, we propose a vibrotactile stimulation system to provide the feedback of ankle joint position, and validate the necessity of combining it with volitional myoelectric control to achieve improved control performance. The stimulation system is wearable and consists of six vibrators. Three of the vibrators are placed on the anterior side of the thigh and the other three on the posterior side of the thigh. To explore the potential of applying the proposed vibrotactile feedback system for prosthetic ankle control, eight able-bodied subjects and two transtibial amputee subjects (TT1 and TT2) were recruited in this research, and several experiments were designed to investigate subjects’ sensitivities to discrete and continuous vibration stimulations applied on the thigh. Then, we proposed a stimulation controller to produce different stimulation patterns according to current ankle angle. Amputee subjects were asked to control a virtual ankle displayed on the computer screen to reach different target ankle angles with a myoelectric controller, and control performances under different feedback conditions were compared. Experimental results indicated that subjects were more sensitive to stimulation position changes (identification accuracies were 96.39 ± 0.86, 91.11, and 93.89% for able-bodied subjects, TT1, and TT2, respectively) than stimulation amplitude changes (identification accuracies were 89.89 ± 2.40, 87.04, and 85.19% for able-bodied subjects, TT1, and TT2, respectively). Response times of able-bodied subjects, TT1, and TT2 to stimulation pattern changes were 0.47 ± 0.02 s, 0.53 s, and 0.48 s, respectively. Furthermore, for both TT1 and TT2, the absolute error of virtual ankle control reduced by about 50% with the addition of vibrotactile feedback. These results suggest that it is promising to apply the vibrotactile feedback system for the control of robotic transtibial prostheses.

Metabolic cost of level-ground walking with a robotic transtibial prosthesis combining push-off power and nonlinear damping behaviors: preliminary results.

Recent advances in robotic technology are facilitating the development of robotic prostheses. Our previous studies proposed a lightweight robotic transtibial prosthesis with a damping control strategy. To improve the performance of power assistance, in this paper, we redesign the prosthesis and improve the control strategy by supplying extra push-off power. A male transtibial amputee subject volunteered to participate in the study. Preliminary experimental results show that the proposed prosthesis with push-off control improves energy expenditure by a percentage ranged from 9.72 % to 14.99 % for level-ground walking compared with the one using non-push-off control.

Noncontact Capacitive Sensing-Based Locomotion Transition Recognition for Amputees With Robotic Transtibial Prostheses.

Recent advancement of robotic transtibial prostheses can restore human ankle dynamics in different terrains. Automatic locomotion transitions of the prosthesis guarantee the amputee's safety and smooth motion. In this paper, we present a noncontact capacitive sensing-based approach for recognizing locomotion transitions of amputees with robotic transtibial prostheses. The proposed sensing system is designed with flexible printed circuit boards which solves the walking instability brought by our previous system when using robotic prosthesis and improves the recognition performance. Six transtibial amputees were recruited and performed tasks of ten locomotion transitions with the robotic prosthesis that we recently constructed. The capacitive sensing system was integrated on the prosthesis and worked in combination with on-prosthesis mechanical sensors. With the cascaded classification method, the proposed system achieved 95.8% average recognition accuracy by support vector machine (SVM) classifier and 94.9% accuracy by quadratic discriminant analysis (QDA) classifier. It could accurately recognize the upcoming locomotion modes from the stance phase of the transition steps. In addition, we proved that adding capacitance signals could significantly reduce recognition errors of the robotic prosthesis in locomotion transition tasks. Our study suggests that the fusion of capacitive sensing system and mechanical sensors is a promising alternative for controlling the robotic transtibial prosthesis.

Walk the Walk: A Lightweight Active Transtibial Prosthesis

Active transtibial prostheses that can overcome the deficiencies of passive prostheses are gaining popularity in the research field. In addition to the advantages in joint torque and gait symmetry, terrain adaptation and total weight are other benefits that can help push active prostheses into the commercial market. In this article, we present a lightweight robotic transtibial prosthesis with damping behaviors for terrain adaptation. The proposed prosthesis, which mainly consists of a low-power motor, weighs only 1.3 kg, excluding the battery. It focuses on terrain adaptation instead of providing positive work at the stance phase. A damping control strategy is proposed to enable the prosthesis to manipulate the ankle impedance during stance with little power consumption. Experiments with three amputee subjects using the robotic prosthesis on different terrains show similar angle trajectories to the intact limb during the controlled flexion (CF) period as well as improved gait symmetry and walking stability compared with the robotic prosthesis in the maximal damping mode. The average power consumption of the prosthesis during one gait cycle is around 3.5 W, and a 0.28-kg rechargeable lithium-ion (Li-ion) battery can sustain a usage duration of more than 12 h or 20,000 steps.

Adaptive Slope Walking With a Robotic Transtibial Prosthesis Based on Volitional EMG Control

Allowing amputees to volitionally control robotic prostheses can improve the adaptability to terrain changes. In this paper, we propose a myoelectric controller for a robotic transtibial prosthesis to realize adaptive slope walking. It works together with the intrinsic controller, enabling amputee users to pay relatively less attention on myoelectric control during walking. Amputee users convey the information of ground slope to prostheses by consciously performing dorsiflexion and plantar flexion of the “phantom ankle” with different intensities at the beginning of the swing phase. Two channels of surface electromyographic signals are measured from the residual shank, and they are mapped to the inclination angle of the slope. Control parameters of the intrinsic controller are then calculated according to the estimated inclination angle. In this preliminary study, two transtibial amputee subjects were recruited. They were asked to convey six targeted inclination angles ( $\bf \pm 5^{\circ}$ , $\bf \pm 10^{\circ}$ , and $\bf \pm 15^{\circ}$ ) to the prosthesis with the trained myoelectric controller during level-ground walking, and satisfactory control performance was achieved. This experiment was designed to simulate the scenario of transiting from level-ground walking to slope walking. Experimental results of controlling the robotic prosthesis to walk on level ground and slopes further verified that it is promising for amputees to adaptively walk on the ground with varied inclination angles in daily life.

Combining human volitional control with intrinsic controller on robotic prosthesis: A case study on adaptive slope walking.

Affording lower-limb amputees the ability to volitionally control robotic prostheses can improve the adaptability to terrain changes as well as enhancing proprioception. However, it also increases amputees' conscious burdens for prosthesis control. Therefore, in this paper, we aim to propose a hybrid controller which combines human volitional control with the intrinsic controller on the robotic transtibial prosthesis, enabling the amputee actively controlling prosthesis with little conscious attention. In this preliminary study, a hybrid controller for adaptive slope walking was designed. A slope estimator was embedded in the intrinsic controller to estimate the ground slope of the previous step using signals measured by prosthetic sensors. And a myoelectric controller allows the amputee subject to convey slope changes to prosthetic controller by volitionally contract his residual muscles, whose electromyography signals were mapped to the slope increment. The hybrid controller combined these two results to obtain the estimated slope. One male transtibial amputee subject was recruited in this research. Experiment results showed that the intrinsic slope estimator produced satisfactory estimation results with an average absolute error of 0.70 ± 0.54 degrees. By adding amputee's volitional control, the hybrid controller is able to predict the upcoming slope changes.

Fuzzy-Logic-Based Terrain Identification with Multisensor Fusion for Transtibial Amputees

Terrain identification is essential for the control of robotic transtibial prostheses to realize smooth locomotion transitions. In this paper, we present a real-time fuzzy-logic-based terrain identification method with multisensor fusion. Five locomotion features, including the foot inclination angle at the first strike, the shank inclination angle at the first strike, foot strike sequence, the foot inclination angle at mid-stance, and the shank inclination angle at toe-off, are used to identify different terrains and terrain transitions. These features are measured by the fusion of two triaxis gyroscopes, two triaxis accelerometers, two force sensitive resistors, and a timer, which can be embedded into the prosthesis. Based on these features, a fuzzy-logic-based identification method is proposed to identify five terrains: level ground, stair ascent, stair descent, ramp ascent, and ramp descent. Moreover, a transition constraint function is developed to improve the identification performance. The execution time of the identification method is 0.79 ms ± 0.02 ms (mean ± standard error of mean) and continuous terrain identification results show that the method can be operated online in real time. The average identification accuracy of 98.74% ± 0.32% is obtained from experiments with six able-bodied and three amputee subjects during steady locomotion periods (no terrain transition). In locomotion transition periods, all the eight transitions we studied are correctly identified and the average identification delay is 9.06% ± 3.46% of one gait cycle.

Effects of toe stiffness on ankle kinetics in a robotic transtibial prosthesis during level-ground walking

Robotic transtibial prostheses are gaining popularity, as they significantly improve amputees’ locomotion. Existing studies mainly concentrate on the importance of ankle joints in these prostheses. However, there are few studies that focus on the effects of prosthetic toe joints. Different from human feet, most prosthetic feet are single-segment structures without toe joints. In order to develop more human-like prostheses with ankle and toe joints, it is of great importance to investigate the effects of toe stiffness on ankle kinetics, as it contributes to the design and control optimizations. In this paper, we analyze the effects of toe stiffness on ankle kinetics in a robotic transtibial prosthesis we have built recently. Dynamic models of the prosthesis’ ankle and toe joints are built. The imposed plantar pressures and objective joint angles of these models are obtained from locomotion experiments on able-bodied subjects. Simulation results indicate when the toe joint is fixed, the ankle energy consumption in one gait cycle is almost 1.2 times of that when the toe joint is driven to track the able-bodied toe motion. Experiments of the prosthesis prototype are carried out on an amputee subject with a transtibial amputation. The results show that compared with the fixed toe joint either the active toe joint or the passive toe joint can reduce the ankle output moment and power consumption. This means adding a toe joint to the foot can reduce the designing requirements of the ankle joint. In addition, the active toe joint can help the prosthesis perform more human-like behaviors compared with the passive toe joint. On the other hand, the passive toe joint can simplify the prosthesis structures and reduce the total weight compared with the active toe joint.

A Hierarchical Control Scheme for Smooth Transitions between Level Ground and Ramps with a Robotic Transtibial Prosthesis

This paper presents a hierarchical control scheme for a robotic transtibial prosthesis to realize smooth locomotion transitions between level ground and ramps. The high level controller identifies current terrain with a fuzzy logic based method and decides the corresponding parameters for lower level controllers. The middle level controller detects different gait phases of one gait cycle on a specific terrain and decides which control method to be used for the current phase. Based on the identified terrain and gait phase, the low level controller performs damping control for controlled plantarflexion/dorsiflexion, and angle control for the swing phase. To evaluate the effectiveness of the proposed control scheme, we design and construct a robotic transtibial prosthesis prototype. Experimental results on normalized stance time, normalized peak ground reaction force, and center of pressure shift in anterior/posterior show improved gait symmetry and walking stability of an amputee subject on ramps with the proposed control scheme. A 17-s long trial that includes different terrains and terrain transitions indicates that the proposed scheme can realize smooth locomotion transitions between level ground and ramps.

An Active Foot-Ankle Prosthesis With Biomechanical Energy Regeneration

A unique, robust, robotic transtibial prosthesis with regenerative kinetics was successfully built and a 6-month human subject trial was conducted on one male below-the-knee amputee under linear walking conditions. This paper presents the quasistatic system modeling, DC motor and transmission modeling and analyses, design methodology, and model verification. It also outlines an approach to the design and development of a robotic transtibial prosthesis. The test data will show that the true power and energy requirement predicted in the modeling and analyses is in good agreement with the measured data, verifying that the approach satisfactorily captures the physical system. The modeling and analyses in this paper describes a process to determine an optimal combination of motors, springs, gearboxes, and rotary to linear transmissions to significantly minimize the power and energy consumption. This kinetic minimization allows the downsizing of the actuation system and the battery required for daily use to a self-portable level.