Abstract

This study focuses on the comparative evaluation of self-aligned (S-A) and alignment-free (A-F) mechanisms for upper limb rehabilitation robots, aiming to improve comfort and adaptability in rehabilitation exercises. The manuscript introduces a detailed analysis of the kinematic adaptability and interaction forces and torques associated with the 3Ra3P and 3Ra2R1P configurations, providing critical insights into their respective strengths and limitations. The methods include kinematic modeling and experimental evaluation of interaction forces during rehabilitation tasks, specifically “eating” and “combing” movements. Key findings reveal that the alignment-free design demonstrated superior adaptability to complex movement trajectories, allowing greater joint displacement and enhanced flexibility. However, this increased adaptability was associated with higher interaction forces and torques, indicating increased resistance and reduced compatibility. Conversely, the self-aligned design exhibited lower interaction forces, suggesting a smoother and more controlled rehabilitation experience, but with reduced flexibility. These insights emphasize the importance of selecting the appropriate design based on specific rehabilitation objectives. The implications of this work are significant for the development of personalized rehabilitation systems, as it highlights the trade-offs between adaptability and resistance in robotic assistance, guiding clinicians in optimizing rehabilitation protocols for individual patient needs.

References

1.
Prendes
,
C. F.
,
Rantner
,
B.
,
Hamwi
,
T.
,
Stana
,
J.
,
Feigin
,
V. L.
,
Stavroulakis
,
K.
, and
Tsilimparis
,
N.
,
2024
, “
Burden of Stroke in Europe: An Analysis of the Global Burden of Disease Study Findings From 2010 to 2019
,”
Stroke
,
55
(
2
), pp.
432
442
.
2.
Ito
,
D.
,
Fukuda
,
M.
,
Hosoi
,
Y.
,
Hirose
,
R.
,
Teramae
,
T.
,
Kamimoto
,
T.
,
Yamada
,
Y.
,
Tsuji
,
T.
,
Noda
,
T.
, and
Kawakami
,
M.
,
2024
, “
Optimizing Shoulder Elevation Assist Rate in Exoskeletal Rehabilitation Based on Muscular Activity Indices: A Clinical Feasibility Study
,”
BMC Neurol.
,
24
(
1
), p.
144
.
3.
Mousley
,
J. J.
,
Gill
,
S. D.
, and
Page
,
R. S.
,
2023
, “
Rehabilitation for Total Shoulder Replacement: An Australian Perspective
,”
ANZ J. Surg.
,
93
(
6
),
1471
1473
.
4.
Ahmed
,
A. F.
,
Lohre
,
R.
, and
Elhassan
,
B. T.
,
2023
, “
Muscular Retraining and Rehabilitation After Shoulder Muscle Tendon Transfer
,”
Phys. Med. Rehabil. Clin. N. Am.
,
34
(
2
), pp.
481
488
.
5.
Ryul
,
L. J.
, and
Min
,
C. Y.
,
2023
, “
Robot-Assisted Orthopedic Surgeries Around the Shoulder Joint: Where We Are?
,”
Biomed. Eng. Lett.
,
13
(
4
), pp.
553
559
.
6.
Zeldin
,
E. R.
,
Boyette
,
D. M.
, and
Norbury
,
J. W.
,
2023
, “
Shoulder Pain After Influenza Vaccine Administration
,”
Am. J. Phys. Med. Rehabil.
,
102
(
10
), pp.
e141
e143
. DOI:10.1097/PHM.0000000000002242
7.
Chao
,
Z. T.
, and
Guo
,
H. R.
,
2023
, “
Reliability and Validity of the Quick Disabilities of the Arm, Shoulder, and Hand Questionnaire in Taiwan
,”
Arch. Phys. Med. Rehabil.
,
104
(
3
), p.
e49
.
8.
Podschun
,
L.
,
Hill
,
C.
,
Kolber
,
M. J.
, and
McClure
,
P.
,
2024
, “
Application of the Staged Approach for Rehabilitation Classification System and Associated Improvements in Patient-Reported Outcomes Following Rehabilitation for Shoulder Pain
,”
Phys. Ther.
,
104
(
5
), p.
pzae029
.
9.
Perry
,
J. C.
,
Rosen
,
J.
, and
Burns
,
S.
,
2007
, “
Upper-Limb Powered Exoskeleton Design
,”
IEEE/ASME Trans. Mechatron.
,
12
(
4
), pp.
408
417
.
10.
Nelson
,
A.
,
Singh
,
G.
,
Robucci
,
R.
,
Patel
,
C.
, and
Banerjee
,
N.
,
2015
, “
Adaptive and Personalized Gesture Recognition Using Textile Capacitive Sensor Arrays
,”
IEEE Trans. Multi-Scale Comput. Syst.
,
1
(
2
), pp.
62
75
.
11.
Florian
,
G.
,
Armin
,
W.
, and
Martin
,
S.
,
2016
, “
Hybrid Neuroprosthesis for the Upper Limb: Combining Brain-Controlled Neuromuscular Stimulation With a Multi-Joint Arm Exoskeleton
,”
Front. Neurosci.
,
10
(
3
), p.
367
. doi.org/10.3389/fnins.2016.00367
12.
Miyauchi
,
H.
,
Iwasaki
,
W.
, and
Kaneko
,
S.
,
2023
, “
Comparison Between Radial Pressure Wave Therapy and Stretching on Shoulder Range of Motion of Horizontal Flexion and Internal Rotation
,”
Sci. Res. Phys. Ther.
,
14
(
1
), pp.
41
46
. DOI:10.57476/srpt.14.1_14_41
13.
Hussain
,
S.
,
Xie
,
S. Q.
,
Jamwal
,
P. K.
, and
Parsons
,
J.
,
2012
, “
An Intrinsically Compliant Robotic Orthosis for Treadmill Training
,”
Med. Eng. Phys.
,
34
(
10
), pp.
1448
1453
.
14.
Wu
,
M.
,
George Hornby
,
T.
,
Landry
,
J. M.
,
Roth
,
H.
, and
Schmit
,
B. D.
,
2011
, “
A Cable-Driven Locomotor Training System for Restoration of Gait in Human SCI
,”
Gait Post.
,
33
(
2
), pp.
256
260
.
15.
Stegall
,
P.
,
Winfree
,
K.
,
Zanotto
,
D.
, and
Agrawal
,
S. K.
,
2013
, “
Rehabilitation Exoskeleton Design: Exploring the Effect of the Anterior Lunge Degree of Freedom
,”
IEEE Trans. Rob.
,
29
(
4
), pp.
838
846
.
16.
Ren
,
Y.
,
Kang
,
S. H.
,
Park
,
H.-S.
,
Wu
,
Y.-N.
, and
Zhang
,
L.-Q.
,
2012
, “
Developing a Multi-Joint Upper Limb Exoskeleton Robot for Diagnosis, Therapy, and Outcome Evaluation in Neurorehabilitation
,”
IEEE Trans. Neural Syst. Rehabil. Eng.
,
21
(
3
), pp.
490
499
.
17.
Awad
,
M. I.
,
Hussain
,
I.
,
Ghosh
,
S.
,
Zweiri
,
Y.
, and
Gan
,
D.
,
2021
, “
A Double-Layered Elbow Exoskeleton Interface With 3-PRR Planar Parallel Mechanism for Axis Self-Alignment
,”
ASME J. Mech. Rob.
,
13
(
1
), p.
011016
.
18.
Grimm
,
F.
,
Naros
,
G.
, and
Gharabaghi
,
A.
,
2016
, “
Compensation or Restoration: Closed-Loop Feedback of Movement Quality for Assisted Reach-to-Grasp Exercises With a Multi-Joint arm Exoskeleton
,”
Front. Neurosci.
,
10
, p.
280
.
19.
Otten
,
A.
,
Voort
,
C.
,
Stienen
,
A.
,
Aarts
,
R.
,
van Asseldonk
,
E.
, and
van der Kooij
,
H.
,
2015
, “
LIMPACT: A Hydraulically Powered Self-Aligning Upper Limb Exoskeleton
,”
IEEE/ASME Trans. Mechatron.
,
20
(
5
), pp.
2285
2298
.
20.
Zhang
,
X.
,
Chen
,
X.
,
Huo
,
B.
,
Liu
,
C.
,
Zhu
,
X.
,
Zu
,
Y.
,
Wang
,
X.
,
Chen
,
X.
, and
Sun
,
Q.
,
2023
, “
An Integrated Evaluation Approach of Wearable Lower Limb Exoskeletons for Human Performance Augmentation
,”
Sci. Rep.
,
13
(
1
), p.
4251
.
21.
Jarrasse
,
N.
, and
Morel
,
G.
,
2013
, “
Connecting a Human Limb to an Exoskeleton
,”
IEEE Trans. Rob.
,
28
(
3
), pp.
697
709
. 10.1109/TRO.2011.2178151Int. J. Adv. Rob. Syst.
22.
Li
,
J.
,
Zhang
,
Z.
,
Tao
,
C.
, and
Ji
,
R.
,
2017
, “
A Number Synthesis Method of the Self-Adapting Upper-Limb Rehabilitation Exoskeletons
,”
Int. J. Adv. Rob. Syst.
,
14
(
3
), p.
1729881417710796
. DOI: 10.1177/1729881417710796
23.
Jianfeng
,
L.
,
Qiang
,
C.
, and
Mingjie
,
D.
,
2020
, “
Compatibility Evaluation of a 4-DOF Ergonomic Exoskeleton for Upper Limb Rehabilitation
,”
Mech. Mach. Theory
,
156
, p.
104146
. DOI:10.1016/j.mechmachtheory.2020.104146
24.
Kim
,
B.
, and
Deshpande
,
A. D.
,
2017
, “
An Upper-Body Rehabilitation Exoskeleton Harmony With an Anatomical Shoulder Mechanism: Design, Modeling, Control, and Performance Evaluation
,”
Int. J. Rob. Res.
,
36
(
4
), pp.
414
435
.
25.
Christensen
,
S.
, and
Bai
,
S.
,
2018
, “
Kinematic Analysis and Design of a Novel Shoulder Exoskeleton Using a Double Parallelogram Linkage
,”
ASME J. Mech. Rob.
,
10
(
4
), p.
041008
.
26.
Peng
,
Y.
,
Bu
,
W.
, and
Chen
,
J.
,
2022
, “
Design of the Wearable Spatial Gravity Balance Mechanism
,”
ASME J. Mech. Rob.
,
14
(
3
), p.
031006
.
27.
Yu
,
Z.
,
Zhao
,
J.
,
Chen
,
D.
,
Chen
,
S.
, and
Wang
,
X.
,
2023
, “
Adaptive Gait Trajectory and Event Prediction of Lower Limb Exoskeletons for Various Terrains Using Reinforcement Learning
,”
J. Intell. Rob. Syst.
,
109
(
2
), p.
23
.
28.
Shen
,
H.
,
Liu
,
X.
,
Liu
,
K.
,
Yao
,
Y.
,
Weng
,
X.
, and
Yang
,
L.
,
2024
, “
Research on Compliant Human–Robot Interaction Based on Admittance Control Strategy for Shoulder Rehabilitation Exoskeleton With CGH Self-Alignment Function
,”
Int. J. Intell. Rob. Appl.
,
8
(
3
), pp.
692
708
.
29.
Li
,
N.
,
Yang
,
T.
,
Yang
,
Y.
,
Chen
,
W.
,
Yu
,
P.
,
Zhang
,
C.
,
Xi
,
N.
,
Zhao
,
Y.
, and
Wang
,
W.
,
2023
, “
Designing Unpowered Shoulder Complex Exoskeleton via Contralateral Drive for Self-Rehabilitation of Post-Stroke Hemiparesis
,”
J. Bionic Eng.
,
20
(
3
), pp.
992
1007
.
30.
Zhang
,
C.
,
Dong
,
M.
,
Li
,
J.
, and
Cao
,
Q.
,
2020
, “
A Modified Kinematic Model of Shoulder Complex Based on Vicon Motion Capturing System: Generalized GH Joint With Floating Centre
,”
Sensors
,
20
(
13
), p.
3713
.
31.
Klopcar
,
N.
, and
Lenarcic
,
J.
,
2006
, “
Bilateral and Unilateral Shoulder Girdle Kinematics During Humeral Elevation
,”
Int. J. Clin. Biomech.
,
21
(
1
), pp.
20
26
.
32.
Newkirk
,
J. T.
,
Tomšič
,
M.
,
Crowell
,
C. R.
,
Villano
,
M. A.
, and
Stanišić
,
M. M.
,
2013
, “
Measurement and Quantification of Gross Human Shoulder Motion
,”
Appl. Bionics Biomech.
,
10
(
4
), pp.
159
173
.
33.
Li
,
J.
,
Zhang
,
C.
,
Dong
,
M.
, and
Cao
,
Q.
,
2020
, “
A Kinematic Model of the Shoulder Complex Obtained From a Wearable Detection System
,”
Appl. Sci.
,
10
(
11
), p.
3696
.
34.
Klamroth-Marganska
,
V.
,
Blanco
,
J.
,
Campen
,
K.
,
Curt
,
A.
,
Dietz
,
V.
,
Ettlin
,
T.
,
Felder
,
M.
, et al
,
2014
, “
Three-Dimensional, Task-Specific Robot Therapy of the Arm After Stroke: a Multicentre, Parallel-Group Randomised Trial
,”
Lancet Neurol.
,
13
(
2
), pp.
159
166
.
35.
Calabrò
,
R. S.
,
Russo
,
M.
,
Naro
,
A.
,
Milardi
,
D.
,
Balletta
,
T.
,
Leo
,
A.
,
Filoni
,
S.
, and
Bramanti
,
P.
,
2016
, “
Who May Benefit From Armeo Power Treatment? A Neurophysiological Approach to Predict Neurorehabilitation Outcomes
,”
PM&R
,
8
(
10
), pp.
971
978
.
36.
Akhmetov
,
V. S.
,
Bucciarelli
,
B.
,
Crosta
,
M.
,
Lattanzi
,
M. G.
,
Spagna
,
A.
,
Fiorentin
,
P. R.
, and
Yu Bannikova
,
E.
,
2024
, “
A New Kinematic Model of the Galaxy: Analysis of the Stellar Velocity Field From Gaia Data Release 3
,”
Mon. Not. R. Astron. Soc.
,
530
(
1
), pp.
710
729
.
37.
Blache
,
Y.
,
Rogowski
,
I.
,
Degot
,
M.
,
Trama
,
R.
, and
Dumas
,
R.
,
2022
, “
Uncertainty Analysis and Sensitivity of Scapulothoracic Joint Angles to Kinematic Model Parameters
,”
Med. Biol. Eng. Comput.
,
60
(
7
), pp.
2065
2075
.
38.
Park
,
H.-S.
,
Ren
,
Y.
, and
Zhang
,
L.-Q.
,
2008
, “
IntelliArm: An Exoskeleton for Diagnosis and Treatment of Patients With Neurological Impairments
,”
2008 Second IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics
,
Scottsdale, AZ
, pp.
109
114
.
39.
Hortal
,
E.
,
Planelles
,
D.
,
Resquin
,
F.
,
Climent
,
J. M.
,
Azorín
,
J. M.
, and
Pons
,
J. L.
,
2015
, “
Using a Brain-Machine Interface to Control a Hybrid Upper Limb Exoskeleton During Rehabilitation of Patients With Neurological Conditions
,”
J. Neuroeng. Rehabil.
,
12
(
1
), pp.
1
16
.
40.
Li
,
J.
,
Cao
,
Q.
,
Zhang
,
C.
,
Tao
,
C.
, and
Ji
,
R.
,
2019
, “
Position Solution of a Novel Four-DOFs Self-Aligning Exoskeleton Mechanism for Upper Limb Rehabilitation
,”
Mech. Mach. Theory
,
141
, pp.
14
39
.
41.
Nam
,
Y.
,
Yang
,
S.
,
Kim
,
J.
,
Koo
,
B.
,
Song
,
S.
, and
Kim
,
Y.
,
2023
, “
Quantification of Comfort for the Development of Binding Parts in a Standing Rehabilitation Robot
,”
Sensors
,
23
(
4
), p.
2206
.
You do not currently have access to this content.