Lower-Limb Prostheses and Exoskeletons With Energy Regeneration: Mechatronic Design and Optimization Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lower-limb biomechatronic devices (i.e., prostheses and exoskeletons) depend upon onboard batteries to power wearable sensors, actuators, and microprocessors, therein inherently limiting their operating durations. Regenerative braking, also termed electrical energy regeneration, represents a promising solution to the aforementioned shortcomings. Regenerative braking converts the otherwise dissipated mechanical energy during locomotion into electrical energy for recharging the onboard batteries, while simultaneously providing negative mechanical work for controlled system deceleration. This paper reviewed the electromechanical design and optimization of lower-limb biomechatronic devices with electrical energy regeneration. The technical review starts by examining human walking biomechanics (i.e., mechanical work, power, and torque about the hip, knee, and ankle joints) and proposes general design principles for regenerative braking prostheses and exoskeletons. Analogous to electric and hybrid electric vehicle powertrains, there are numerous mechatronic design components that could be optimized to maximize electrical energy regeneration, including the mechanical power transmission, electromagnetic machine, electrical drive, device mass and moment of inertia, and energy storage devices. Design optimization of these system components is individually discussed while referencing the latest advancements in robotics and automotive engineering. The technical review demonstrated that existing systems (1) are limited to level-ground walking applications and (2) have maximum energy regeneration efficiencies between 30% and 37%. Accordingly, potential future directions for research and innovation include (1) regenerative braking during dynamic movements like sitting down and slope and staircase descent and (2) utilizing high-torque-density electromagnetic machines and low-impedance mechanical power transmissions to maximize energy regeneration efficiencies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it