1
|
Carriere J, Shafi H, Brehon K, Pohar Manhas K, Churchill K, Ho C, Tavakoli M. Case Report: Utilizing AI and NLP to Assist with Healthcare and Rehabilitation During the COVID-19 Pandemic. Front Artif Intell 2021; 4:613637. [PMID: 33733232 PMCID: PMC7907599 DOI: 10.3389/frai.2021.613637] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 01/08/2021] [Indexed: 01/16/2023] Open
Abstract
The COVID-19 pandemic has profoundly affected healthcare systems and healthcare delivery worldwide. Policy makers are utilizing social distancing and isolation policies to reduce the risk of transmission and spread of COVID-19, while the research, development, and testing of antiviral treatments and vaccines are ongoing. As part of these isolation policies, in-person healthcare delivery has been reduced, or eliminated, to avoid the risk of COVID-19 infection in high-risk and vulnerable populations, particularly those with comorbidities. Clinicians, occupational therapists, and physiotherapists have traditionally relied on in-person diagnosis and treatment of acute and chronic musculoskeletal (MSK) and neurological conditions and illnesses. The assessment and rehabilitation of persons with acute and chronic conditions has, therefore, been particularly impacted during the pandemic. This article presents a perspective on how Artificial Intelligence and Machine Learning (AI/ML) technologies, such as Natural Language Processing (NLP), can be used to assist with assessment and rehabilitation for acute and chronic conditions.
Collapse
Affiliation(s)
- Jay Carriere
- Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
| | - Hareem Shafi
- Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
| | - Katelyn Brehon
- School of Public Health, University of Alberta, Edmonton, AB, Canada
| | - Kiran Pohar Manhas
- Neurosciences, Rehabilitation, and Vision Strategic Clinical Network, Alberta Health Services, Calgary, AB, Canada
| | - Katie Churchill
- Department of Occupational Therapy, University of Alberta, Edmonton, AB, Canada.,Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Chester Ho
- Neurosciences, Rehabilitation, and Vision Strategic Clinical Network, Alberta Health Services, Calgary, AB, Canada.,Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada
| | - Mahdi Tavakoli
- Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
| |
Collapse
|
2
|
Fong J, Ocampo R, Gross DP, Tavakoli M. Intelligent Robotics Incorporating Machine Learning Algorithms for Improving Functional Capacity Evaluation and Occupational Rehabilitation. JOURNAL OF OCCUPATIONAL REHABILITATION 2020; 30:362-370. [PMID: 32253595 DOI: 10.1007/s10926-020-09888-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Introduction Occupational rehabilitation often involves functional capacity evaluations (FCE) that use simulated work tasks to assess work ability. Currently, there exists no single, streamlined solution to simulate all or a large number of standard work tasks. Such a system would improve FCE and functional rehabilitation through simulating reaching maneuvers and more dexterous functional tasks that are typical of workplace activities. This paper reviews efforts to develop robotic FCE solutions that incorporate machine learning algorithms. Methods We reviewed the literature regarding rehabilitation robotics, with an emphasis on novel techniques incorporating robotics and machine learning into FCE. Results Rehabilitation robotics aims to improve the assessment and rehabilitation of injured workers by providing methods for easily simulating workplace tasks using intelligent robotic systems. Machine learning-based approaches combine the benefits of robotic systems with the expertise and experience of human therapists. These innovations have the potential to improve the quantification of function as well as learn the haptic interactions provided by therapists to assist patients during assessment and rehabilitation. This is done by allowing a robot to learn based on a therapist's motions ("demonstrations") what the desired workplace activity ("task") is and how to recreate it for a worker with an injury ("patient"). Through Telerehabilitation and internet connectivity, these robotic assessment techniques can be used over a distance to reach rural and remote locations. Conclusions While the research is in the early stages, robotics with integrated machine learning algorithms have great potential for improving traditional FCE practice.
Collapse
Affiliation(s)
- Jason Fong
- Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
| | - Renz Ocampo
- Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
| | - Douglas P Gross
- Department of Physical Therapy, University of Alberta, 2-50 Corbett Hall, Alberta,, T6G 2G4, Edmonton, Canada.
| | - Mahdi Tavakoli
- Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
| |
Collapse
|
3
|
Gassert R, Dietz V. Rehabilitation robots for the treatment of sensorimotor deficits: a neurophysiological perspective. J Neuroeng Rehabil 2018; 15:46. [PMID: 29866106 PMCID: PMC5987585 DOI: 10.1186/s12984-018-0383-x] [Citation(s) in RCA: 145] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2018] [Accepted: 05/07/2018] [Indexed: 11/30/2022] Open
Abstract
The past decades have seen rapid and vast developments of robots for the rehabilitation of sensorimotor deficits after damage to the central nervous system (CNS). Many of these innovations were technology-driven, limiting their clinical application and impact. Yet, rehabilitation robots should be designed on the basis of neurophysiological insights underlying normal and impaired sensorimotor functions, which requires interdisciplinary collaboration and background knowledge. Recovery of sensorimotor function after CNS damage is based on the exploitation of neuroplasticity, with a focus on the rehabilitation of movements needed for self-independence. This requires a physiological limb muscle activation that can be achieved through functional arm/hand and leg movement exercises and the activation of appropriate peripheral receptors. Such considerations have already led to the development of innovative rehabilitation robots with advanced interaction control schemes and the use of integrated sensors to continuously monitor and adapt the support to the actual state of patients, but many challenges remain. For a positive impact on outcome of function, rehabilitation approaches should be based on neurophysiological and clinical insights, keeping in mind that recovery of function is limited. Consequently, the design of rehabilitation robots requires a combination of specialized engineering and neurophysiological knowledge. When appropriately applied, robot-assisted therapy can provide a number of advantages over conventional approaches, including a standardized training environment, adaptable support and the ability to increase therapy intensity and dose, while reducing the physical burden on therapists. Rehabilitation robots are thus an ideal means to complement conventional therapy in the clinic, and bear great potential for continued therapy and assistance at home using simpler devices. This review summarizes the evolution of the field of rehabilitation robotics, as well as the current state of clinical evidence. It highlights fundamental neurophysiological factors influencing the recovery of sensorimotor function after a stroke or spinal cord injury, and discusses their implications for the development of effective rehabilitation robots. It thus provides insights on essential neurophysiological mechanisms to be considered for a successful development and clinical inclusion of robots in rehabilitation.
Collapse
Affiliation(s)
- Roger Gassert
- Department of Health Sciences and Technology, ETH Zurich, 8092, Zurich, Switzerland.
| | - Volker Dietz
- Spinal Cord Injury Center, Balgrist University Hospital, 8008, Zurich, Switzerland
| |
Collapse
|
4
|
Current Trends in Robot-Assisted Upper-Limb Stroke Rehabilitation: Promoting Patient Engagement in Therapy. CURRENT PHYSICAL MEDICINE AND REHABILITATION REPORTS 2014; 2:184-195. [PMID: 26005600 DOI: 10.1007/s40141-014-0056-z] [Citation(s) in RCA: 88] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Stroke is one of the leading causes of long-term disability today; therefore, many research efforts are focused on designing maximally effective and efficient treatment methods. In particular, robotic stroke rehabilitation has received significant attention for upper-limb therapy due to its ability to provide high-intensity repetitive movement therapy with less effort than would be required for traditional methods. Recent research has focused on increasing patient engagement in therapy, which has been shown to be important for inducing neural plasticity to facilitate recovery. Robotic therapy devices enable unique methods for promoting patient engagement by providing assistance only as needed and by detecting patient movement intent to drive to the device. Use of these methods has demonstrated improvements in functional outcomes, but careful comparisons between methods remain to be done. Future work should include controlled clinical trials and comparisons of effectiveness of different methods for patients with different abilities and needs in order to inform future development of patient-specific therapeutic protocols.
Collapse
|
5
|
Van der Loos HFM, Worthen-Chaudhari L, Schwandt D, Bevly DM, Kautz SA. A split-crank bicycle ergometer uses servomotors to provide programmable pedal forces for studies in human biomechanics. IEEE Trans Neural Syst Rehabil Eng 2010; 18:445-52. [PMID: 20378483 DOI: 10.1109/tnsre.2010.2047586] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
This paper presents a novel computer-controlled bicycle ergometer, the TiltCycle, for use in human biomechanics studies of locomotion. The TiltCycle has a tilting (reclining) seat and backboard, a split pedal crankshaft to isolate the left and right loads to the feet of the pedaler, and two belt-driven, computer-controlled motors to provide assistance or resistance loads independently to each crank. Sensors measure the kinematics and force production of the legs to calculate work performed, and the system allows for goniometric and electromyography signals to be recorded. The technical description presented includes the mechanical design, low-level software and control algorithms, system identification and validation test results.
Collapse
Affiliation(s)
- H F Machiel Van der Loos
- Department of Mechanical Engineering, University of British Columbia, Vancouver, BC V6T1ZT, Canada.
| | | | | | | | | |
Collapse
|
6
|
Gupta A, O'Malley MK, Patoglu V, Burgar C. Design, Control and Performance of RiceWrist: A Force Feedback Wrist Exoskeleton for Rehabilitation and Training. Int J Rob Res 2008. [DOI: 10.1177/0278364907084261] [Citation(s) in RCA: 170] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
This paper presents the design, control and performance of a high fidelity four degree-of-freedom wrist exoskeleton robot, RiceWrist, for training and rehabilitation. The RiceWrist is intended to provide kinesthetic feedback during the training of motor skills or rehabilitation of reaching movements. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuries. The exoskeleton device accommodates forearm supination and pronation, wrist flexion and extension and radial and ulnar deviation in a compact parallel mechanism design with low friction, zero backlash and high stiffness. As compared to other exoskeleton devices, the RiceWrist allows easy measurement of human joint angles and independent kinesthetic feedback to individual human joints. In this paper, joint-space as well as task-space position controllers and an impedance-based force controller for the device are presented. The kinematic performance of the device is characterized in terms of its workspace, singularities, manipulability, backlash and backdrivability. The dynamic performance of RiceWrist is characterized in terms of motor torque output, joint friction, step responses, behavior under closed loop set-point and trajectory tracking control and display of virtual walls. The device is singularity-free, encompasses most of the natural workspace of the human joints and exhibits low friction, zero-backlash and high manipulability, which are kinematic properties that characterize a high-quality impedance display device. In addition, the device displays fast, accurate response under position control that matches human actuation bandwidth and the capability to display sufficiently hard contact with little coupling between controlled degrees-of-freedom.
Collapse
Affiliation(s)
- Abhishek Gupta
- Department of Mechanical Engineering and Materials Science Rice University, Houston, TX 77005, USA,
| | - Marcia K. O'Malley
- Department of Mechanical Engineering and Materials Science Rice University, Houston, TX 77005, USA,
| | - Volkan Patoglu
- Faculty of Engineering and Natural Sciences Sabanci University Tuzla, Istanbul 34956, Turkey,
| | | |
Collapse
|
7
|
Fu Y, Zhang F, Ma X, Meng Q. Development of a CPM Machine for Injured Fingers. CONFERENCE PROCEEDINGS : ... ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL CONFERENCE 2007; 2005:5017-20. [PMID: 17281372 DOI: 10.1109/iembs.2005.1615602] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Human fingers are easy to be injured. A CPM machine is a mechanism based on the rehabilitation theory of continuous passive motion (CPM). To develop a CPM machine for the clinic application in the rehabilitation of injured fingers is a significant task. Therefore, based on the theories of evidence based medicine (EBM) and CPM, we've developed a set of biomimetic mechanism after modeling the motions of fingers and analyzing its kinematics and dynamics analysis. We also design an embedded operating system based on ARM (a kind of 32-bit RISC microprocessor). The equipment can achieve the precise control of moving scope of fingers, finger's force and speed. It can serves as a rational checking method and a way of assessment for functional rehabilitation of human hands. Now, the first prototype has been finished and will start the clinical testing in Harbin Medical University shortly.
Collapse
Affiliation(s)
- Yili Fu
- Robotics Inst., Harbin Inst. of Technol
| | | | | | | |
Collapse
|
8
|
Korb W, Marmulla R, Raczkowsky J, Mühling J, Hassfeld S. Robots in the operating theatre—chances and challenges. Int J Oral Maxillofac Surg 2004; 33:721-32. [PMID: 15556318 DOI: 10.1016/j.ijom.2004.03.015] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/29/2004] [Indexed: 10/26/2022]
Abstract
The use of surgical robots and manipulators is still being frequently discussed in the mass media as well as in the scientific community. Although it was already noted in 1985 that the first patient was treated by a joint team of robot and surgeon, today such systems are not routinely used. This can be explained by the high complexity of such systems and the often limited usability, but also, that it is difficult for surgeons to accept "automatic" machines. In this paper the possibilities and chances of robots and manipulators will be explained and it will be shown that robots will never work alone in the operating theatre as it is common in industry today. On the other hand, also limitations and challenges will be outlined. Therefore first a review on today's systems is given in different disciplines including oral- and cranio-maxillofacial surgery, then advantages and disadvantages are shown.
Collapse
Affiliation(s)
- W Korb
- Department of Maxillofacial and Craniofacial Surgery, University Hospital, D-69120 Heidelberg, Germany.
| | | | | | | | | |
Collapse
|
9
|
Lum PS, Burgar CG, Kenney DE, Van der Loos HF. Quantification of force abnormalities during passive and active-assisted upper-limb reaching movements in post-stroke hemiparesis. IEEE Trans Biomed Eng 1999; 46:652-62. [PMID: 10356872 DOI: 10.1109/10.764942] [Citation(s) in RCA: 100] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We evaluated a method for measuring abnormal upper-limb motor performance in post-stroke hemiparetic subjects. A servomechanism (MIME) moved the forearm in simple planar trajectories, directly controlling hand position and forearm orientation. Design specifications are presented, along with system performance data during an initial test of 13 stroke subjects with a wide range of impairment levels. Performance of subjects was quantified by measuring the forces and torques between the paretic limb and the servomechanism as the subjects relaxed (passive), or attempted to generate force in the direction of movement (active). During passive movements, the more severely impaired subjects resisted movement, producing higher levels of negative work than less-impaired subjects and neurologically normal controls. During active movements, the more severely impaired subjects produced forces with larger directional errors, and were less efficient in producing work. These metrics had significant test-retest repeatability. These motor performance metrics can potentially detect smaller within-subject changes than motor function scales. This method could complement currently used measurement tools for the evaluation of subjects during recovery from stroke, or during therapeutic interventions.
Collapse
Affiliation(s)
- P S Lum
- Veterans Affairs Palo Alto Health Care System, Rehabilitation Research and Development Center, CA 94304, USA.
| | | | | | | |
Collapse
|
10
|
Erlandson R. Applications of robotic/mechatronic systems in special education, rehabilitation therapy, and vocational training: a paradigm shift. ACTA ACUST UNITED AC 1995. [DOI: 10.1109/86.372889] [Citation(s) in RCA: 17] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
|
11
|
Lum P, Reinkensmeyer D, Lehman S. Robotic assist devices for bimanual physical therapy: preliminary experiments. ACTA ACUST UNITED AC 1993. [DOI: 10.1109/86.279267] [Citation(s) in RCA: 74] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
|
12
|
Preising B, Hsia T, Mittelstadt B. A literature review: robots in medicine. ACTA ACUST UNITED AC 1991; 10:13-22. [DOI: 10.1109/51.82001] [Citation(s) in RCA: 46] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
|