Journal of NeuroEngineering and Rehabilitation | |
Assessing walking ability using a robotic gait trainer: opportunities and limitations of assist-as-needed control in spinal cord injury | |
Research | |
Lars Lünenburger1  Serena Maggioni2  Alejandro Melendez-Calderon3  Robert Riener4  Marc Bolliger5  Armin Curt5  | |
[1] ETH Transfer, ETH Zurich, Zurich, Switzerland;Hocoma AG, Volketswil, Switzerland;School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia;School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia;Jamieson Trauma Institute, Metro North Health, Brisbane, Australia;Sensory-Motor Systems (SMS) Lab, ETH Zurich, Zurich, Switzerland;Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland;Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland; | |
关键词: Assist-as-needed; Lokomat; Robotic gait training; Rehabilitation; Gait; Walking; Spinal cord injury; Assessment; | |
DOI : 10.1186/s12984-023-01226-4 | |
received in 2022-05-06, accepted in 2023-07-27, 发布年份 2023 | |
来源: Springer | |
【 摘 要 】
BackgroundWalking impairments are a common consequence of neurological disorders and are assessed with clinical scores that suffer from several limitations. Robot-assisted locomotor training is becoming an established clinical practice. Besides training, these devices could be used for assessing walking ability in a controlled environment. Here, we propose an adaptive assist-as-needed (AAN) control for a treadmill-based robotic exoskeleton, the Lokomat, that reduces the support of the device (body weight support and impedance of the robotic joints) based on the ability of the patient to follow a gait pattern displayed on screen. We hypothesize that the converged values of robotic support provide valid and reliable information about individuals’ walking ability.MethodsFifteen participants with spinal cord injury and twelve controls used the AAN software in the Lokomat twice within a week and were assessed using clinical scores (10MWT, TUG). We used a regression method to identify the robotic measure that could provide the most relevant information about walking ability and determined the test–retest reliability. We also checked whether this result could be extrapolated to non-ambulatory and to unimpaired subjects.ResultsThe AAN controller could be used in patients with different injury severity levels. A linear model based on one variable (robotic knee stiffness at terminal swing) could explain 74% of the variance in the 10MWT and 61% in the TUG in ambulatory patients and showed good relative reliability but poor absolute reliability. Adding the variable ‘maximum hip flexor torque’ to the model increased the explained variance above 85%. This did not extend to non-ambulatory nor to able-bodied individuals, where variables related to stance phase and to push-off phase seem more relevant.ConclusionsThe novel AAN software for the Lokomat can be used to quantify the support required by a patient while performing robotic gait training. The adaptive software might enable more challenging training conditions tuned to the ability of the individuals. While the current implementation is not ready for assessment in clinical practice, we could demonstrate that this approach is safe, and it could be integrated as assist-as-needed training, rather than as assessment.Trial registrationClinicalTrials.gov Identifier: NCT02425332.
【 授权许可】
CC BY
© BioMed Central Ltd., part of Springer Nature 2023
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
RO202310116823271ZK.pdf | 5205KB | download | |
MediaObjects/13041_2023_1055_MOESM3_ESM.docx | 1174KB | Other | download |
13690_2023_1170_Article_IEq32.gif | 1KB | Image | download |
104KB | Image | download | |
42004_2023_990_Article_IEq37.gif | 1KB | Image | download |
40708_2023_202_Article_IEq10.gif | 1KB | Image | download |
40708_2023_202_Article_IEq25.gif | 1KB | Image | download |
Fig. 1 | 253KB | Image | download |
Fig. 2 | 92KB | Image | download |
Fig. 3 | 49KB | Image | download |
Fig. 2 | 915KB | Image | download |
Fig. 4 | 364KB | Image | download |
MediaObjects/12951_2023_2053_MOESM1_ESM.docx | 3328KB | Other | download |
MediaObjects/41016_2023_340_MOESM1_ESM.docx | 14KB | Other | download |
Fig.1 | 290KB | Image | download |
40798_2023_628_Figg_HTML.png | 5KB | Image | download |
Fig. 1 | 146KB | Image | download |
Fig. 2 | 342KB | Image | download |
Fig. 3 | 137KB | Image | download |
Fig. 4 | 153KB | Image | download |
Fig. 7 | 1273KB | Image | download |
13690_2023_1170_Article_IEq185.gif | 1KB | Image | download |
MediaObjects/12888_2023_5170_MOESM2_ESM.docx | 955KB | Other | download |
13690_2023_1170_Article_IEq188.gif | 1KB | Image | download |
12888_2023_5142_Article_IEq3.gif | 1KB | Image | download |
12888_2023_5142_Article_IEq16.gif | 1KB | Image | download |
12888_2023_5142_Article_IEq17.gif | 1KB | Image | download |
12888_2023_5142_Article_IEq18.gif | 1KB | Image | download |
12888_2023_5142_Article_IEq21.gif | 1KB | Image | download |
12888_2023_5142_Article_IEq23.gif | 1KB | Image | download |
13690_2023_1170_Article_IEq211.gif | 1KB | Image | download |
MediaObjects/13100_2023_299_MOESM6_ESM.xlsx | 21KB | Other | download |
13690_2023_1170_Article_IEq212.gif | 1KB | Image | download |
Fig. 1 | 379KB | Image | download |
Fig. 1 | 629KB | Image | download |
MediaObjects/12888_2023_5142_MOESM1_ESM.pdf | 126KB | download | |
Fig. 4 | 547KB | Image | download |
12888_2023_5172_Article_IEq4.gif | 1KB | Image | download |
Fig. 3 | 110KB | Image | download |
Fig. 42 | 79KB | Image | download |
Fig. 3 | 298KB | Image | download |
【 图 表 】
Fig. 3
Fig. 42
Fig. 3
12888_2023_5172_Article_IEq4.gif
Fig. 4
Fig. 1
Fig. 1
13690_2023_1170_Article_IEq212.gif
13690_2023_1170_Article_IEq211.gif
12888_2023_5142_Article_IEq23.gif
12888_2023_5142_Article_IEq21.gif
12888_2023_5142_Article_IEq18.gif
12888_2023_5142_Article_IEq17.gif
12888_2023_5142_Article_IEq16.gif
12888_2023_5142_Article_IEq3.gif
13690_2023_1170_Article_IEq188.gif
13690_2023_1170_Article_IEq185.gif
Fig. 7
Fig. 4
Fig. 3
Fig. 2
Fig. 1
40798_2023_628_Figg_HTML.png
Fig.1
Fig. 4
Fig. 2
Fig. 3
Fig. 2
Fig. 1
40708_2023_202_Article_IEq25.gif
40708_2023_202_Article_IEq10.gif
42004_2023_990_Article_IEq37.gif
13690_2023_1170_Article_IEq32.gif
【 参考文献 】
- [1]
- [2]
- [3]
- [4]
- [5]
- [6]
- [7]
- [8]
- [9]
- [10]
- [11]
- [12]
- [13]
- [14]
- [15]
- [16]
- [17]
- [18]
- [19]
- [20]
- [21]
- [22]
- [23]
- [24]
- [25]
- [26]
- [27]
- [28]
- [29]
- [30]
- [31]
- [32]
- [33]
- [34]
- [35]
- [36]
- [37]
- [38]
- [39]
- [40]
- [41]
- [42]
- [43]
- [44]
- [45]
- [46]
- [47]
- [48]
- [49]
- [50]
- [51]
- [52]
- [53]
- [54]
- [55]
- [56]
- [57]
- [58]
- [59]
- [60]
- [61]
- [62]
- [63]
- [64]
- [65]
- [66]
- [67]
- [68]
- [69]
- [70]
- [71]
- [72]
- [73]
- [74]