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Delayed Output Feedback Control for Gait Assistance and Resistance Using a Robotic Exoskeleton Bokman Lim, Junwon Jang, Jusuk Lee, Ryungjune Choi, Younbaek Lee, and Youngbo Shim Abstract—In this study, we propose an interaction control framework for gait assistance and resistance using a robotic exoskeleton. We define ...
izing oscillatory systems under certain conditions [18]–[20]. By adding a timedelay buffer to the self-feedback control loop, we can generate assistive or resistive torque stably in the interaction between the user and exoskeleton. The proposed interaction controller can operate at various gait speeds and under environ...
the current sample time and i-1 is the previous sample time. The current smoothed state $y^i$ is expressed as a weighted sum of the previous sample time state $y^{i-1}$ and the original state value of the current sample time $y^i_{raw}$ , and the smoothing rate can be adjusted by changing the smoothing factor $\...
) are difficult to find. Rather, it is known that metabolic energy greatly increases due to increases in weight and motion constraints due to a rigid frame and actuator structure covering the knee [22]–[24]. The increase in metabolic energy during the device's operation implies that it is a burden to the user even to w...
2.94 | 0.3 | | 5 | 3.87 | 3.63 | 6.3 | | Mean (±SD) | 3.45±0.56 | $3.55 \pm 0.52$ | -3.4±6.5 † | NMR: net metabolic rate; rNMR: reduced net metabolic rate from free walking condition (No exo). $^\dagger p$ - value = 0.4 > 0.05 for paired t-t...
The treadmill speed increased from 1 km/h to 5 km/h in 1 km/h increments. The torque and power generated in the hip joint were calculated with a sensor attached to the exoskeleton. As shown in Fig. 5(b), the time-delay $\Delta t$ affects the generated torque magnitude, even though it is a control variable related to...
$\kappa_2 = 9.5$ | 4.30 | 8.29 | 3.24 | -10.1 | | $\kappa_3 = 11.0$ | 4.78 | 9.30 | 3.07 | -14.8 | | $\kappa_4 = 12.5$ | 5.22 | 10.36 | 2.98 | -17.1 | | $\kappa_5 = 14.0$ | 5.70 | 11.34 | 2.85 | -20.9 | τRMS ...
motion (or range of motion) determines the output torque profile. As shown in Fig. 10(c), the generated torque trajectory changed with changes to the gait environment. Without changing the control parameters ( $\Delta t = 0.25~\rm s$ , $\kappa = -4$ ), the generated torque and power values varied with notable differe...
MEDICAL ROBOTS Human-in-the-loop optimization of hip assistance with a soft exosuit during walking Ye Ding, 1,2* Myunghee Kim, 1,2* Scott Kuindersma, 1† Conor J. Walsh 1,2† Wearable robotic devices have been shown to substantially reduce the energy expenditure of human walking. However, response variance between partic...
). Although these achievements are impressive, there remain opportunities to explore different wearable assistive hardware, control parameterizations, applications to other joints, and alternative optimization methods that could improve sample efficiency. We developed an experimental method to rapidly identify optimal ...
.2% of the conventional gait cycle, defined with heel strike as 0% (table S2). The offset timing was constrained to occur at least 15% later than the peak timing. The range and constraint of peak and offset timing (Fig. 2C) were chosen by slightly extending the average range of the biological hip extension moment (32) ...
To quantitatively summarize the differences between the participants' metabolic landscapes, we computed the probability that each participant's optimal parameters would reduce the metabolic cost of other participants according to each participant's posterior landscape (Fig. 4, D to F). This analysis suggested that, in...
a noisy respiratory signal as the objective function of the optimization indicates that this method can be applied to other alternate physiological or biological signals, such as using kinematic symmetry to optimize wearable devices for poststroke patients or using balancerelated measurements to optimize prostheses. T...
the previous two steps, the reference force profile was scaled for each stride. The actual force signal was measured by two load cells (LSB200, FUTEK Advanced Sensor Technology) placed in series with the Bowden cables on each leg. Combined with the actuator position signals measured by the encoders (AS5134, Ams) mount...
}) + \varepsilon, \varepsilon \sim N(0, \sigma_{\text{noise}}^2)$$ (4) where $\sigma_{\text{noise}}^2$ is the noise variance. Given the Gaussian process prior and data set D, the posterior metabolic cost distribution $f_^{\text{inst}}$ was calculated for a parameter $\mathbf{x}_$ as $f_^{\text{inst}}(\mathbf{x}...
protocol, where the net metabolic rate of the second no-suit condition increased by 32.4% compared with the first no-suit condition. Convergence time analysis The convergence time for each participant was calculated in a post hoc analysis (fig. S3 and table S4). We defined the convergence of the optimization with the ...
The Effect of Hip Assistance Levels on Human Energetic Cost Using Robotic Hip Exoskeletons Inseung Kang ®, Hsiang Hsu ®, and Aaron Young, Member, IEEE Abstract—In order for the lower limb exoskeletons to realize their considerable potential, a greater understanding of optimal assistive performance is required. While ot...
storing the mechanical energy to perform positive joint power. However, due to different muscle characteristics and the lack of efficient elastic storage elements, the hip joint requires higher energetic cost for similar mechanical joint power [20]. Therefore, the hip joint represents an important area of exploration ...
n}}$$ (2) Using the both equations, our device can support approximately 90% of peak and maximum continuous torque for an average body mass of 70 kg subject walking at 1.2 m/s. The device allows 100° and 30° range of motion in the sagittal plane for maximum hip flexion and extension respectively. Additionally, a passi...
3). Over a gait cycle, the controller can generate a torque assistance for both hip flexion and extension with predefined control parameters. The three key parameters that dictate the assistance profile are onset timing, assistance duration, and assistance magnitude. The onset timing parameter was used with values fou...
keleton without the SEA), exoskeleton in zero impedance mode, and no exoskeleton condition. We have added the actu- Fig. 4. Initial human characterization results of the exoskeleton device. (A) Actuator interaction torque compensation. When the actuator operates with zero impedance mode, the interaction torque (shown...
assistance duration window length was swept from 20% to 35% of the gait cycle with a 5% increment. The metabolic cost reduction for each condition was 6.2% for 20%, 14.6% for 25%, 11.2% for 30%, and 11.0% for 35% all relative to metabolic cost of walking in zero impedance mode. As the 25% window length achieved the hi...
measured using the device's SEA and encoder during walking in each condition. All of the joint kinematic and kinetic results are represented with an averaged value across 10 subjects. Flexion and extension joint torques were decoupled by computing the torque during flexion ( $45\% \sim 70\%$ ) and extension ( $90\% \s...
relationship (R2 = 0.999). The stride frequency in zero impedance mode correlated well with human biomechanics data with the same walking speed [28]. A video of a subject walking in a marching gait pattern with hip assistance at maximal levels is included in the supplemental material. VI. DISCUSSION Overall, our exosk...
. Future exoskeleton designers can utilize our findings to further investigate to optimize the mechatronic design for a more robust and versatile exoskeleton. Lastly, implementation of an integrated controller capable of scaling parameters dynamically may aid the exoskeleton technology to be translated to more realisti...
RESEARCH ARTICLE Comparing optimized exoskeleton assistance of the hip, knee, and ankle in single and multi-joint configurations Patrick W. Franks\* , Gwendolyn M. Bryan, Russell M. Martin , Ricardo Reyes, Ava C. Lakmazaheri and Steven H. Collins Department of Mechanical Engineering, Stanford University, Stanford, Cal...
et al., 2014; Collins et al., 2015; Seo et al., 2016; Quinlivan et al., 2017; Zhang et al., 2017; Ding et al., 2018; Lee et al., 2018; Malcolm et al., 2018; Lim et al., 2019; MacLean and Ferris, 2019; Cao et al., 2020; Sawicki et al., 2020). The largest metabolic cost reductions have been around 18% relative to walkin...
this study was to find the single-joint, two-joint, and whole-leg exoskeleton torques that minimized the metabolic cost of walking and to understand how effective each device architecture is at assisting walking. We used a tethered hip–knee–ankle exoskeleton emulator that can assist hip flexion and extension, knee fle...
., 2020). This device can apply large torques using offboard motors and Bowden cable transmissions to actuate an end effector worn by the user, enabling laboratory tests of different assistance strategies without actuation limits (Caputo and Collins, 2014). The device has a worn mass of 13.5 kg. It has carbon fiber str...
impedance controller being turned on and off as a function of percent stride defined by the nodes while the knee angle was nonzero, resulting in discrete jumps in desired torque. testing. Before this, one participant completed a 9-parameter whole-leg optimization pilot study (Supplementary Material, Section 14), which...
parameter pilot study (Supplementary Material, Section 14). For whole-leg optimization for P1, initial values were based on the optimized values for single-joint assistance. For P2, P3, and P4, initial values for optimization were based on the optimized values for P1. Finally, for the two-joint assistance optimizations...
was calculated using indirect calorimetry. We measured volumetric carbon dioxide expulsion, oxygen consumption, and breath duration on a breath-by-breath basis (Quark CPET, COSMED). For each condition, we calculated metabolic rate using a modified Brockway equation (Brockway, 1987) similar to previous studies (Zhang e...
assistance reduced metabolic cost for each participant, with an average reduction of 13% relative to walking with no torque, although this was not statistically significant (N = 3, range of reductions: 5–18%, p = .07). Ankle-only assistance performed best of the single-joint strategies, reducing metabolic cost by 30% ...
knees, whole-leg assistance optimized to smaller magnitudes than single-joint assistance. For the ankles, maximum torque had to be constrained to find comfortable profiles for walking. Ankle torques were limited to 1 Nm/kg for single-joint assistance, and 0.8 Nm/kg for two-joint and whole-leg assistance. in multi-join...
7; Ding et al., 2018; Lim et al., 2019). This corresponded to a 33% reduction relative to walking with no exoskeleton, much greater than the just-noticeable difference in metabolic cost (20%) (Medrano et al., 2020), indicating that participants could feel the reduction in effort compared to walking normally. Because wh...
user bent more into flexion, allowing for a "stabilizing" effect that prevented buckling of the knee. In this study, we used a tethered exoskeleton emulator to compare assistance, but future work should attempt to recreate this assistance on mobile exoskeletons. We reported our improvements primarily relative to walki...
studying two-joint exoskeleton assistance could confirm the results found here. These results suggest that new cost functions, gait environments, and user populations could be exciting topics for future studies. Future work could optimize metabolic cost alongside other costs that are important for gait, such as walkin...
Task-agnostic exoskeleton control via biological joint moment estimation https://doi.org/10.1038/s41586-024-08157-7 Received: 17 October 2023 Accepted: 4 October 2024 Published online: 13 November 2024 Dean D. Molinaro1,2,5,8 ⋈, Keaton L. Scherpereel1,2,6,8, Ethan B. Schonhaut1, Georgios Evangelopoulos3,7, Max K. Shep...
13,37-39}$ . Additionally, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA. Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, USA. 3X, The Moonshot Factory, Mountain View, CA, USA. 4College of Engineering, Bouvé College ...
, Nanchang) mounted coaxially with the hip and knee provided up to 15 N m of assistance at each joint. The semirigid structure consisted of carbon fibre and 3D printed nylon orthotics on which the actuators and sensors were mounted. Six inertial measurement units (IMUs), joint encoders on the hips and knees, and a pair...
knee moments significantly better than the baseline method for both cyclic (hip R2 0.79, knee R2 0.86) and impedance-like activities (hip R2 0.81, knee R2 0.87) without any participant-specific calibration (Fig. 3b,c). Representative time series are shown in Fig. 3d–f. Comparing within each activity, our estimator sig...
described in Extended Data Table 2, that had not been previously tested or analysed (Supplementary Fig. 1 and Supplementary Video 5). These tasks were intentionally designed to be highly unique from the original dataset to push the limits of our approach, including burpees, mimicking a basketball layup and walking on ...
, these results demonstrate the ability of our approach to autonomously modulate assistance across tasks in a beneficial manner, a critical hurdle in developing task-agnostic exoskeleton controllers. To further quantify the effect of the device during transient tasks, we measured metabolic cost for three participants p...
any user-specific calibration or hand-engineered state machine criteria. Whereas recent work has demonstrated how to leverage instantaneous joint moment estimates as a promising alternative for exoskeleton control during walking13,14,35,36, here we present the missing piece: task generalization. Specifically, our deep...
. H., Wiggin, M. B. & Sawicki, G. S. Reducing the energy cost of human walking using an unpowered exoskeleton. Nature 522, 212–215 (2015). 18. Yang, J., Park, J., Kim, J., Park, S. & Lee, G. Reducing the energy cost of running using a lightweight, low-profile elastic exosuit. J. NeuroEngineering Rehabil. 18, 129 (2021)...
doi.org/10.1109/JBHI.2023.3262164 (2023). 35. Lin, J., Divekar, N. V., Thomas, G. C. & Gregg, R. D. Optimally biomimetic passivity-based control of a lower-limb exoskeleton over the primary activities of daily life. IEEE Open J. Control Syst. 1, 15–28 (2022). 36. Zhang, J., Lin, J., Peddinti, V. & Gregg, R. D. Optimal ...
© The Author(s), under exclusive licence to Springer Nature Limited 2024 Methods Autonomous robotic hip–knee exoskeleton In this study, we used the clothing-integrated robotic exoskeleton developed at X, which was designed to enhance human mobility by providing powered sagittal-plane assistance to the hips and knees (d...
were then delayed by 100 and 50 ms, respectively. This delay was chosen at the knee because 50 ms was the minimum possible delay to guarantee a consistent relationship between biological joint moment estimates and exoskeleton assistance owing to limitations in loop rate reliability of the exoskeleton. Hip assistance w...
the hyperparameter optimization to conduct a forward activity selection optimization (Extended Data Fig. 3a). During each optimization step, the TCN was trained and tested using leave-one-participant-out validation to compute the expected model performance when evaluated on a new participant. First, model performance ...
oders indicated that our six-axis IMUs did not fully capture the relevant kinematic input information. Overall, the IMUs contributed the most to the accuracy of the model, followed by the encoders and, last, the insole. Previous work has shown that kinematic sensors can be effectively used to estimate GRFs, indicating ...
actuated exoskeleton data as well as the unactuated data. Phase 2: training data with pilot model In phase 2, five new participants (four males, one female, age of 23.4 ± 4.9 years, height of 171.4 ± 7.4 cm and body mass of 68.0 ± 12.7 kg) participated in a single day protocol similar to phase 1. However, during phase...
while wearing the exoskeleton controlled with the task-agnostic controller. Exoskeleton assistance was sequentially ramped up in four evenly spaced increments every 2 min until the participant reached full torque assistance. The participant then walked at full assistance (20 and 15% of the estimated biological hip and...
training data includes 15 users performing all 66 conditions from the 28 task groups (Extended Data Fig. 2). The first 10 users include both unactuated data for all tasks and actuated data for those that could be mimicked with a heuristic controller. The following five users include actuated data for all tasks using a...
gait. J. Appl. Physiol. 117, 1406–1415 (2014). Acknowledgements We acknowledge E. Rouse and K. Zealand for their contribution to the overarching technical direction; and A. Azocar, A. Memo and R. Jackson for their contribution to experimental design and analysis. In addition, E. Lamers, T. Malko, A. Metzger, N. Hite,...
R2 , (c) hip RMSE, (d) knee RMSE, (e) hip normalized MAE, and (f) knee normalized MAE of our joint moment estimator is shown for each activity and is compared to the baseline method. The MAE results are normalized to their corresponding peak-to-peak range of the ground-truth joint moments. The bars depict the inter-su...
| 0.15 | | L1 KernelRegularization | [1e-5, 1e-3] | 0 | 0 | | L2 KernelRegularization ...
Human-in-the-Loop Optimization of Hip Exoskeleton Assistance During Stair Climbing Dongho Park , Jimin An, Dawit Lee , Inseung Kang , Member, IEEE, and Aaron J. Young , Senior Member, IEEE Abstract—Objective: This study applies human-in-theloop optimization to identify optimal hip exoskeleton assistance patterns for st...
control parameters efficiently. In contrast to traditional parameter tuning approaches, such as grid search or sequential optimization, which becomes impractical as the number of parameters increases, HILO leverages statistical models and optimization algorithms to search the high-dimensional parameter space efficient...
ators are connected to lightweight, L-shaped carbon fiber pelvic interfaces, ensuring a secure fit while maintaining alignment between the actuator axes and the user's hip joint centers during use. The pelvis interfaces are designed to encompass the lateral sides and back of the user's pelvis. The back of the interface...
findings, it can be inferred that the optimal extension torque for a more demanding task like stair climbing would likely exceed the maximum torque capacity of 15 Nm of the exoskeleton used in this study. Therefore, to ensure that the exoskeleton can meet the requirements of stair climbing and maximize the reduction i...
truth. The metabolic cost was then estimated using data from the beginning of the trial with varying durations. The results show that using 2.6 minutes of data yields an estimation error of less than 2%, providing a balance between accuracy and experimental feasibility for the optimization protocol. On the second day,...
covariance function k(x, x-), where x and xare parameter settings. The surrogate model was iteratively updated based on observations from user trials, guiding the selection of new parameter values to evaluate. The EI acquisition function at any point x can be expressed as: $$EI(x) = \mathbb{E}[\max(f(x_{\text{best}}) ...
need for accurate metabolic rate estimation against the practical limitations imposed by the task's physical demands. The adaptation of short-duration metabolic rate estimation methods to stair climbing optimization is feasible with an adjusted measurement interval. By extending the estimation window to 2.6 minutes, w...
112). C. Bayesian Optimization Convergence Analysis The Bayesian optimization process for hip exoskeleton control parameters ran for 20 iterations. Metabolic rate convergence, based on our predefined criterion of three consecutive iterations showing a change of 0.5% or less, was achieved after 18 iterations (Fig. 6). R...
have generally reported later peak flexion timing in optimized profiles compared to biological moments [12]. However, our findings differ in terms of flexion duration. While previous level walking studies found longer flexion duration in optimized profiles, our results for stair climbing showed a shorter flexion durat...
metabolic cost reduction compared to others. These findings suggest that the parameter space for effective exoskeleton assistance may be relatively broad, with multiple combinations of parameters capable of producing meaningful metabolic benefits. Future studies might benefit from identifying faster-to-measure proxies...
Check for updates EXOSKELETON Estimating human joint moments unifies exoskeleton control, reducing user effort Dean D. Molinaro1,2*, Inseung Kang3, Aaron J. Young1,2 Robotic lower-limb exoskeletons can augment human mobility, but current systems require extensive, context-specific considerations, limiting their real-wo...
to additional tasks where the mapping between foot force sensor measurements and joint moments is more complex. Alternatively, energy-shaping methods have been developed for assisting the hip, knee, and ankle during multiple ambulation modes and during sit-stand cycles (29, 30). These approaches have demonstrated impr...
their hip joint work with that of the exoskeleton (48), reducing their lower-limb positive mechanical work compared with No Exo (H2). In addition, we quantified the accuracy of our deep learningbased hip moment estimator when integrated into the exoskeleton controller (deployed online) during level-ground walking, ram...
mechanical work was measured across the same 10 participants under the Unified Control and No Exo conditions. The unified controller was deployed using the same hip moment estimator that was used when measuring user metabolic cost. As shown in Fig. 3, the total positive mechanical work of the user's lower-limb joints ...
resulting RMSE and $\mathbb{R}^2$ of the TCN and Baseline estimates were computed with respect to the ground-truth hip moments from inverse dynamics. The overall RMSE of the TCN averaged across the five ambulation modes was $0.142 \pm 0.021$ N·m/kg, which was significantly lower than the Baseline method [change of...
means, error bars represent $\pm 1$ SD about the mean, and asterisks indicate statistical significance (P < 0.05). Fig. 5. Representative time series. Examples of hip moments estimated by the TCN and the corresponding ground truth values are shown. (A) Representative strides from 7 of the 13 total level-ground walk...
joint (Fig. 3), with relative reductions of 29.2 and 22.8% relative to No Exo during level-ground walking and ramp ascent, respectively. By delaying the exoskeleton assistance relative to the instantaneous hip moment estimate in the mid-level control layer (Fig. 1 and fig. S4), the unified joint moment controller prov...
of the dataset, meaning that the model interpolated between conditions in the training set well but began to lose performance during extrapolation. We did not find any significant differences in $\mathbb{R}^2$ between holding in and holding out each condition. This suggests that the TCN maintained the correct "shape...
used as TCN training data compatible with our device (35). Specifically, the dataset was collected with the same exoskeleton sensor modalities as those of our custom hip exoskeleton but had different IMU placements. When collecting the dataset, each participant walked over level ground, along four inclines and decline...
the device was used for online TCN deployment. The total exoskeleton mass was 4.8 kg, including electronics and batteries. Additional information is provided in Supplementary Methods and in figs. S1 and S2. Hip moment estimation using a TCN We used a TCN (47) to estimate the exoskeleton user's hip flexion/ extension m...
user. In addition, delays below 35 ms could not be tested because of controller limitations from filter delay and worst-case model inference latency. For the remainder of this study, a programmed delay of 100 ms (total delay of 125 ms including the low-pass filter) was used to minimize overall delay and to align with ...
Exo) across the lower-limb joints (hip, knee, and ankle) were evaluated using a two-way ANOVA for level ground and ramp ascent. Pairwise comparisons were only conducted for testing significant differences between Unified Control and No Exo within each joint. In addition, the total positive lower-limb joint work result...
Optimized Mappings from Biological Hip Moment Estimates to Exoskeleton Torque can Personalize Assistance Across Users and Generalize Across Tasks Justine C. Powell, Ethan B. Schonhaut*, Dean D. Molinaro, and Aaron J. Young, Senior Member, IEEE Abstract—Recent advancements in data-driven methods have enabled real-time ...
with the Georgia Institute of Technology George W. Woodruff School of Mechanical Engineering, Atlanta, GA, 30332. (e-mail: eschonhaut3@gatech.edu). Dean D. Molinaro was with the Georgia Institute of Technology, Institute for Robotics and Intelligent Machines (IRIM) and the George W. Woodruff School of Mechanical Engin...
moment represents an effective method of generalizable exoskeleton control across different tasks and activities [15], [16], studies have shown that providing purely biological joint moment-based assistance is not metabolically optimal during steady state walking [8], [9]. Similarly, pilot studies from our previous wo...
hat{\tau}{bio})$ to exoskeleton assistance torque $(\tau{cmd})$ at a given time (t). The scale $(\alpha)$ term changes the magnitude of torque assistance as the actuator's maximum torque is much less than that of the hip joint. In this experiment, the scale term was not optimized and instead held constant at 20% o...
each ambulation mode across 21 distinct trials, where the exoskeleton assisted the user. During each trial, we collected 90 seconds of sensor data from onboard the exoskeleton and two-minute measurements of metabolic cost via the Parvo metabolic cart (TrueOne 2400, ParvoMedics). Across all subjects and conditions, the...
minimum of one minute of respiratory data [26], [27]. To make comparisons across both subject and walking conditions, we normalized the metabolic data by the no exoskeleton metabolic value using (2), where all metabolic analyses are presented in units of percent change from the no exoskeleton condition (%Δ No-Exo). Fo...
calculated using unilateral data from the exoskeleton's sensors. Torque $(\tau)$ is directly proportional to the motor torque constant, gear ratio, and current measured by the exoskeleton motors. Positive Power (+ P) was calculated using (3) and (4), where $\theta$ represents the angle of rotation of the motor. Sim...
tasks, trends showed that users mostly preferred controller parameters within Quadrant IV, representing longer delay values and smaller shape values, between 59% and 74% of the time compared to other quadrants. C. Exoskeleton Power & Torque We used linear regression to observe the relationship between metabolic cost a...
exoskeleton torque for each subject. The goal was to keep the peak torque relatively constant across all iterations within each ambulation mode. Note: As subject two's exoskeleton data was corrupted for their slower level ground mode, that data was not included in this analysis. Across 9 subjects with 21 iterations of...
the subject is very high. This benefit can be seen in the most physically demanding mode of the experiment at 5°-degree incline walking, where most metabolic reductions occurred at extremely low shape values during walking. Additional evidence is further reflected in user preference, where the level ground and incline...
REVIEW Open Access Review of control strategies for lower-limb exoskeletons to assist gait Romain Baud1 , Ali Reza Manzoori1* , Auke Ijspeert1 and Mohamed Bouri1,2 Abstract Background: Many lower-limb exoskeletons have been developed to assist gait, exhibiting a large range of control methods. The goal of this paper is...
subcategory of partial assistance exoskeletons are the devices that are intended for rehabilitation purposes.1 Here, the ultimate purpose is to train the users to become independent of the assistance ofered by the device. A fundamental distinction can thus be made between the desired outcomes of these exoskeletons ver...
osuits) are included too, even if these are not really stif "skeletons", but closer to "tendons and muscles". Te papers that do not deal directly with an exoskeleton, but suggest a sensing method that could be useful for them are included as well. As explained previously, many gait assistance devices are presented in t...
ing the gait itself Type of publication: peer-reviewed journal or conference article, patent Describes a controller that is impossible to apply outside of a simulated environment Does not give enough details about the control method to fully describe it (typically the case for papers reporting clinical trial outcomes) ...
to human errors which are more likely to happen during demanding tasks, long operation times, or with novice/distracted users. In this case, the challenge is both to make the user interface easy to use to minimize the learning time and the risk of manipulation errors, and also quick to use to avoid losing time in tran...
have also been utilized. Terrain identifcation has recently gained attention in the felds of orthotics and prosthetics, and the body of literature exploring it is relatively small. Even the existing papers are limited to proof of concept implementations, demonstrating the performance of terrain identifcation algorithm...
the forefoot, the late stance can be detected instead of the heel strike [108]. Te reference instant can also be recognized with an inertial measurement unit (IMU) on the shank, when crossing the zero angular speed [109]. A variant is to detect the point of "negative-to-positive power" of the ankle by looking at the a...
], but the details are not clearly documented. Te AFOs strategy is limited to the partial assistance paradigm, since the user needs to be able to initiate the gait and maintain it at least for a few steps. Simple linear increase of the gait phase (LNP) Tis is the simplest way to determine or impose the gait phase. It c...
in the original paper). However, the estimated gait phases have not been used in a controller, but have only been compared to evaluate the estimation accuracy. State machine (FSM) Controllers can switch behavior depending on transitions triggered by events. Tis may be useful because some states of the gait are noncont...
actually using the trajectories recorded from healthy people for patients. In many cases, the trajectories are signifcantly changed or fully generated at runtime, and some papers are completely dedicated to the problem of optimization/ generation of trajectories [190–193]. In some studies, model-based computations [19...
. Te torque profle itself may change over time, and be optimized online [105]. Te torque profle can be as simple as a square pulse [103]. In some studies, the torque profles are fne-tuned ofine based on subjective feedback from the users [136, 212] or previous measurements from the users [169]. In others, they are opti...
terms of the approach to calculating the intended torque from muscle activity, several variants can be distinguished: Te amplifcation of independent muscles activities is typically implemented with one artifcial muscle per biologic muscle [239]. Its advantage is that the cocontraction of the biologic muscles also pro...