Back

Biomechanical Modelling of Sitting Movements for Designing Robotic Lower-Limb Prostheses and Exoskeletons with Energy Regeneration

Laschowski, B.; Sharif Razavian, R.; McPhee, J.

2019-10-10 bioengineering
10.1101/801258 bioRxiv
Show abstract

Although regenerative actuators can extend the operating durations of robotic lower-limb exoskeletons and prostheses, these energy-efficient powertrains have been exclusively designed and evaluated for continuous level-ground walking. ObjectiveHere we analyzed the lower-limb joint mechanical power during stand-to-sit movements using inverse dynamic simulations to estimate the biomechanical energy available for electrical regeneration. MethodsNine subjects performed 20 sitting and standing movements while lower-limb kinematics and ground reaction forces were measured. Subject-specific body segment parameters were estimated using parameter identification, whereby differences in ground reaction forces and moments between the experimental measurements and inverse dynamic simulations were minimized. Joint mechanical power was calculated from net joint torques and rotational velocities and numerically integrated over time to determine joint biomechanical energy. ResultsThe hip produced the largest peak negative mechanical power (1.8 {+/-} 0.5 W/kg), followed by the knee (0.8 {+/-} 0.3 W/kg) and ankle (0.2 {+/-} 0.1 W/kg). Negative mechanical work from the hip, knee, and ankle joints per stand-to-sit movement were 0.35 {+/-} 0.06 J/kg, 0.15 {+/-} 0.08 J/kg, and 0.02 {+/-} 0.01 J/kg, respectively. Conclusion and SignificanceAssuming an 80-kg person and previously published regenerative actuator efficiencies (i.e., maximum 63%), robotic lower-limb exoskeletons and prostheses could theoretically regenerate ~26 Joules of total electrical energy while sitting down, compared to ~19 Joules per walking stride. Given that these regeneration performance calculations are based on healthy young adults, future research should include seniors and/or rehabilitation patients to better estimate the biomechanical energy available for electrical regeneration among individuals with mobility impairments.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 0.1%
22.8%
2
Journal of NeuroEngineering and Rehabilitation
28 papers in training set
Top 0.1%
14.9%
3
PLOS ONE
4510 papers in training set
Top 13%
14.5%
50% of probability mass above
4
Journal of Neural Engineering
197 papers in training set
Top 0.4%
8.5%
5
IEEE Transactions on Neural Systems and Rehabilitation Engineering
40 papers in training set
Top 0.1%
6.5%
6
Annals of Biomedical Engineering
34 papers in training set
Top 0.2%
4.9%
7
IEEE Transactions on Biomedical Engineering
38 papers in training set
Top 0.2%
4.0%
8
Scientific Reports
3102 papers in training set
Top 40%
3.3%
9
PeerJ
261 papers in training set
Top 7%
1.7%
10
Sensors
39 papers in training set
Top 1%
1.3%
11
Journal of Biomechanical Engineering
17 papers in training set
Top 0.2%
1.3%
12
Journal of Biomechanics
57 papers in training set
Top 0.5%
1.1%
13
npj Microgravity
11 papers in training set
Top 0.2%
1.1%
14
Frontiers in Physiology
93 papers in training set
Top 4%
1.0%
15
Bioinspiration & Biomimetics
13 papers in training set
Top 0.2%
0.9%
16
PLOS Computational Biology
1633 papers in training set
Top 23%
0.8%
17
Gait & Posture
22 papers in training set
Top 0.3%
0.8%
18
Journal of the American Medical Directors Association
13 papers in training set
Top 0.3%
0.7%
19
Frontiers in Aging Neuroscience
67 papers in training set
Top 4%
0.5%
20
Royal Society Open Science
193 papers in training set
Top 6%
0.5%
21
Medicine & Science in Sports & Exercise
15 papers in training set
Top 0.6%
0.5%