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Thøgersen MB, Mohammadi M, Gull MA, Bengtson SH, Kobbelgaard FV, Bentsen B, Khan BYA, Severinsen KE, Bai S, Bak T, Moeslund TB, Kanstrup AM, Andreasen Struijk LNS. User Based Development and Test of the EXOTIC Exoskeleton: Empowering Individuals with Tetraplegia Using a Compact, Versatile, 5-DoF Upper Limb Exoskeleton Controlled through Intelligent Semi-Automated Shared Tongue Control. SENSORS (BASEL, SWITZERLAND) 2022; 22:6919. [PMID: 36146260 PMCID: PMC9502221 DOI: 10.3390/s22186919] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 06/16/2023]
Abstract
This paper presents the EXOTIC- a novel assistive upper limb exoskeleton for individuals with complete functional tetraplegia that provides an unprecedented level of versatility and control. The current literature on exoskeletons mainly focuses on the basic technical aspects of exoskeleton design and control while the context in which these exoskeletons should function is less or not prioritized even though it poses important technical requirements. We considered all sources of design requirements, from the basic technical functions to the real-world practical application. The EXOTIC features: (1) a compact, safe, wheelchair-mountable, easy to don and doff exoskeleton capable of facilitating multiple highly desired activities of daily living for individuals with tetraplegia; (2) a semi-automated computer vision guidance system that can be enabled by the user when relevant; (3) a tongue control interface allowing for full, volitional, and continuous control over all possible motions of the exoskeleton. The EXOTIC was tested on ten able-bodied individuals and three users with tetraplegia caused by spinal cord injury. During the tests the EXOTIC succeeded in fully assisting tasks such as drinking and picking up snacks, even for users with complete functional tetraplegia and the need for a ventilator. The users confirmed the usability of the EXOTIC.
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Affiliation(s)
- Mikkel Berg Thøgersen
- Center for Rehabilitation Robotics, Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark
| | - Mostafa Mohammadi
- Center for Rehabilitation Robotics, Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark
| | - Muhammad Ahsan Gull
- Department of Materials and Production Technology, Aalborg University, 9220 Aalborg, Denmark
| | - Stefan Hein Bengtson
- Visual Analysis and Perception (VAP) Lab, Department of Architecture, Design, and Media Technology, Aalborg University, 9000 Aalborg, Denmark
| | | | - Bo Bentsen
- Center for Rehabilitation Robotics, Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark
| | - Benjamin Yamin Ali Khan
- Spinal Cord Injury Centre of Western Denmark, Viborg Regional Hospital, 8800 Viborg, Denmark
| | - Kåre Eg Severinsen
- Spinal Cord Injury Centre of Western Denmark, Viborg Regional Hospital, 8800 Viborg, Denmark
| | - Shaoping Bai
- Department of Materials and Production Technology, Aalborg University, 9220 Aalborg, Denmark
| | - Thomas Bak
- Department of Electronic Systems, Aalborg University, 9220 Aalborg, Denmark
| | - Thomas Baltzer Moeslund
- Visual Analysis and Perception (VAP) Lab, Department of Architecture, Design, and Media Technology, Aalborg University, 9000 Aalborg, Denmark
| | | | - Lotte N. S. Andreasen Struijk
- Center for Rehabilitation Robotics, Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark
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Rulik I, Sunny MSH, Sanjuan De Caro JD, Zarif MII, Brahmi B, Ahamed SI, Schultz K, Wang I, Leheng T, Longxiang JP, Rahman MH. Control of a Wheelchair-Mounted 6DOF Assistive Robot With Chin and Finger Joysticks. Front Robot AI 2022; 9:885610. [PMID: 35937617 PMCID: PMC9354078 DOI: 10.3389/frobt.2022.885610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 06/15/2022] [Indexed: 11/13/2022] Open
Abstract
Throughout the last decade, many assistive robots for people with disabilities have been developed; however, researchers have not fully utilized these robotic technologies to entirely create independent living conditions for people with disabilities, particularly in relation to activities of daily living (ADLs). An assistive system can help satisfy the demands of regular ADLs for people with disabilities. With an increasing shortage of caregivers and a growing number of individuals with impairments and the elderly, assistive robots can help meet future healthcare demands. One of the critical aspects of designing these assistive devices is to improve functional independence while providing an excellent human–machine interface. People with limited upper limb function due to stroke, spinal cord injury, cerebral palsy, amyotrophic lateral sclerosis, and other conditions find the controls of assistive devices such as power wheelchairs difficult to use. Thus, the objective of this research was to design a multimodal control method for robotic self-assistance that could assist individuals with disabilities in performing self-care tasks on a daily basis. In this research, a control framework for two interchangeable operating modes with a finger joystick and a chin joystick is developed where joysticks seamlessly control a wheelchair and a wheelchair-mounted robotic arm. Custom circuitry was developed to complete the control architecture. A user study was conducted to test the robotic system. Ten healthy individuals agreed to perform three tasks using both (chin and finger) joysticks for a total of six tasks with 10 repetitions each. The control method has been tested rigorously, maneuvering the robot at different velocities and under varying payload (1–3.5 lb) conditions. The absolute position accuracy was experimentally found to be approximately 5 mm. The round-trip delay we observed between the commands while controlling the xArm was 4 ms. Tests performed showed that the proposed control system allowed individuals to perform some ADLs such as picking up and placing items with a completion time of less than 1 min for each task and 100% success.
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Affiliation(s)
- Ivan Rulik
- Department of Computer Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
- *Correspondence: Ivan Rulik,
| | - Md Samiul Haque Sunny
- Department of Computer Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
| | | | | | - Brahim Brahmi
- Electrical Engineering Department, Collège Ahuntsic, Montreal, QC, Canada
| | | | - Katie Schultz
- Assistive Technology Program, Clement J. Zablocki VA Medical Center, Milwaukee, WI, United States
| | - Inga Wang
- Department of Rehabilitation Sciences & Technology, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
| | - Tony Leheng
- UFACTORY Technology Co., Ltd., Shenzhen, China
| | | | - Mohammad H. Rahman
- Department of Mechanical Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
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Computer Vision-Based Adaptive Semi-Autonomous Control of an Upper Limb Exoskeleton for Individuals with Tetraplegia. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12094374] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
We propose the use of computer vision for adaptive semi-autonomous control of an upper limb exoskeleton for assisting users with severe tetraplegia to increase independence and quality of life. A tongue-based interface was used together with the semi-autonomous control such that individuals with complete tetraplegia were able to use it despite being paralyzed from the neck down. The semi-autonomous control uses computer vision to detect nearby objects and estimate how to grasp them to assist the user in controlling the exoskeleton. Three control schemes were tested: non-autonomous (i.e., manual control using the tongue) control, semi-autonomous control with a fixed level of autonomy, and a semi-autonomous control with a confidence-based adaptive level of autonomy. Studies on experimental participants with and without tetraplegia were carried out. The control schemes were evaluated both in terms of their performance, such as the time and number of commands needed to complete a given task, as well as ratings from the users. The studies showed a clear and significant improvement in both performance and user ratings when using either of the semi-autonomous control schemes. The adaptive semi-autonomous control outperformed the fixed version in some scenarios, namely, in the more complex tasks and with users with more training in using the system.
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