Evidence map›Paper›PMID 36274915›Full record

ArticleFrontiers in robotics and AI2022

Biomechanical knee energy harvester: Design optimization and testing.

Moran Gad, Ben Lev-Ari, Amir Shapiro, Coral Ben-David, Raziel Riemer

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Moran GadMechanical Engineering Department, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Ben Lev-AriMechanical Engineering Department, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Amir ShapiroMechanical Engineering Department, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Coral Ben-DavidIndustrial Engineering and Management Department of Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Raziel RiemerIndustrial Engineering and Management Department of Ben-Gurion University of the Negev, Beer-Sheva, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biomechanical energy harvesters are designed to generate electrical energy from human locomotion (e.g., walking) with minimal or no additional effort by the users. These harvesters aim to carry out the work of the muscles during phases in locomotion where the muscles are acting as brakes. Currently, many harvesters focus on the knee joint during late swing, which is only one of three phases available during the gait cycle. For the device to be successful, there is a need to consider design components such as the motor/generator and the gear ratio. These components influence the amount of electrical energy that could be harvested, metabolic power during harvesting, and more. These various components make it challenging to achieve the optimal design. This paper presents a design of a knee harvester with a direct drive that enables harvesting both in flexion and extension using optimization. Subsequently, two knee devices were built and tested using five different harvesting levels. Results show that the 30% level was the best, harvesting approximately 5 W of electricity and redacting 8 W of metabolic energy compared to walking with the device as a dead weight. Evaluation of the models used in the optimization showed a good match to the system model but less for the metabolic power model. These results could pave the way for an energy harvester that could utilize more of the negative joint power during the gait cycle while reducing metabolic effort.

Indexed as

biomechanical knee energy harvesterdesign optimizationexoskeletonreduced effortsimulation

Identifiers

PMID36274915
PMCPMC9581163

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.