| Literature DB >> 33105845 |
Andrea Catherine Alarcón-Aldana1, Mauro Callejas-Cuervo2, Antonio Padilha Lanari Bo3.
Abstract
The use of videogames and motion capture systems in rehabilitation contributes to the recovery of the patient. This systematic review aimed to explore the works related to these technologies. The PRISMA method (Preferred Reporting Items for Systematic reviews and Meta-Analyses) was used to search the databases Scopus, PubMed, IEEE Xplore, and Web of Science, taking into consideration four aspects: physical rehabilitation, the use of videogames, motion capture technologies, and upper limb rehabilitation. The literature selection was limited to open access works published between 2015 and 2020, obtaining 19 articles that met the inclusion criteria. The works reported the use of inertial measurement units (37%), a Kinect sensor (48%), and other technologies (15%). It was identified that 26% used commercial products, while 74% were developed independently. Another finding was that 47% of the works focus on post-stroke motor recovery. Finally, diverse studies sought to support physical rehabilitation using motion capture systems incorporating inertial units, which offer precision and accessibility at a low cost. There is a clear need to continue generating proposals that confront the challenges of rehabilitation with technologies which offer precision and healthcare coverage, and which, additionally, integrate elements that foster the patient's motivation and participation.Entities:
Keywords: inertial measurement unit (IMU); inertial sensors; motion capture; physical rehabilitation; serious videogames; state of the art; telerehabilitation; upper limbs
Mesh:
Year: 2020 PMID: 33105845 PMCID: PMC7660052 DOI: 10.3390/s20215989
Source DB: PubMed Journal: Sensors (Basel) ISSN: 1424-8220 Impact factor: 3.576
Search parameters in the different databases.
| Database | Search Parameters |
|---|---|
| Scopus | TITLE-ABS-KEY (((rehabilitation OR health OR “physical therapy” OR “musculoskeletal”) AND (videogames OR “video games” OR “video-games” OR “serious videogames” OR “serious games” OR “serious video games” OR “exergames” OR “exergaming” OR “active videogames”) AND (“upper limb” OR “elbow” OR “shoulder” OR “arm” OR “wrist” OR “humerus”) AND (“inertial sensor” OR “motion capture” OR “motion capture system” OR mocap OR wearable))) AND (LIMIT-TO (PUBYEAR, 2020) OR LIMIT-TO (PUBYEAR, 2019) OR LIMIT-TO (PUBYEAR, 2018) OR LIMIT-TO (PUBYEAR, 2017) OR LIMIT-TO (PUBYEAR, 2016) OR LIMIT-TO (PUBYEAR, 2015)) |
| PubMed | ((rehabilitation OR health OR “physical therapy” OR “musculoskeletal”) AND (videogames OR “video games” OR “video-games” OR “serious videogames” OR “serious games” OR “serious video games” OR “exergames” OR “exergaming” OR “active videogames”) AND (“upper limb” OR “elbow” OR “shoulder” OR “arm” OR “wrist” OR “humerus”) AND (“inertial sensor” OR “motion capture” OR “motion capture system” OR mocap OR wearable)) |
| IEEE Xplore | ((rehabilitation OR health OR “physical AND therapy” OR musculoskeletal) AND (videogames OR “video AND games” OR video-games OR “serious AND videogames” OR “serious AND games” OR “serious AND video AND games” OR exergames OR exergaming OR “active AND videogames”) AND (“upper AND limb” OR “elbow” OR “shoulder” OR “arm” OR “wrist” OR “humerus”) AND (“inertial AND sensor” OR “motion AND capture” OR “mocap” OR “motion AND capture AND system” OR wearable)) |
Figure 1Systematic process used in the selection of articles, based on PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses).
Figure 2Percentage of the use of motion capture systems.
Figure 3Diagnoses in the works analyzed.
Figure 4Percentage of the population involved in the study.
Figure 5Distribution of the technology used.
Figure 6Distribution of the part of the body treated in the study.
Search parameters in the different databases. IMU, inertial measurement unit; MS, Microsoft; ROM, range of motion; N/A, not applicable.
| No. | Mocap System | Clinical Condition | Population (Sample) * | Technology Used ** | Part of the Body Rehabilitated | Reference |
|---|---|---|---|---|---|---|
| 1 | IMU | Cerebral palsy | 19 P | Mixed: Myo bracelet, adapted commercial videogame (Dashy Square and personalized software development) | Hand and wrist | [ |
| 2 | MS HoloLens | ROM | 25 H | Mixed: MS HoloLens and developed videogame | Shoulder | [ |
| 3 | IMU | Stroke | 8 H | Proposed system: an environment of games and software for the therapist | Upper and lower limbs | [ |
| 4 | MS Kinect | Upper limb lesions | 10 P | Mixed: MS Kinect V2, videogame development, and web application | Arm | [ |
| 5 | IMU | N/A | 11 H | Proposed system | Arm | [ |
| 6 | IMU | N/A | N/A | Commercial: ArmeoSenso | N/A | [ |
| 7 | IMU | Upper limb lesions | 10 P | Mixed: Myo bracelet and a developed videogame | Arm | [ |
| 8 | MS Kinect | Stroke | 30 H | Commercial: MS Kinect V2 and Mystic Isle (videogame integrated to Kinect) | Upper part of the human body | [ |
| 9 | MS Kinect | Stroke | 11 P | Mixed: MS Kinect and a developed videogame | Arm | [ |
| 10 | MS Kinect | Stroke | 24 P | Mixed: MS Kinect and Recovery Rapids ™ (personalized videogame) | Arm | [ |
| 11 | MS Kinect | ROM | 10 H | Mixed: MS Kinect and development of a personalized system | Arm | [ |
| 12 | MS Kinect | Friedreich’s ataxia | 27 P, 43 H | Mixed: MS Kinect and development of a videogame. | Arm | [ |
| 13 | IMU | Stroke | 29 P | Commercial: Bimeo | Arm | [ |
| 14 | IMU | Stroke | 11 P | Commercial: ArmeoSenso. | Arm | [ |
| 15 | MS Kinect | Stroke | 74 P | Commercial: JRS Wave | Human body | [ |
| 16 | MS Kinect | Stroke | 18 P, 12 H | Proposed system | Upper part of the human body | [ |
| 17 | MS Kinect | Energy expenditure | 19 H | Mixed: MS Kinect and development of a system | Human body | [ |
| 18 | Other optical systems | Lesions due to brain injury | N/A | Mixed | Hand | [ |
| 19 | Orthosis with IMU | Stroke | 7 P | Proposed system | Wrist and hand | [ |
* Population: P = patients; H = healthy participants. ** Technology used: commercial and/or developed.
Figure 7Main motion capture system methods [33].
Figure 8Paper classification according to the technologies used.