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The desired movement (A), 3D model with supportive parts of the device marked—10: forearm support, 11: proximal finger rest, and 12: distal finger rest (B), and the actual device, moving through its available ROM (C).
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Due to the ageing population and an increasing number of stroke patients, we see the potential future of rehabilitation in telerehabilitation, which might alleviate the workload of physiotherapists and occupational therapists. In order to enable the use of telerehabilitation, devices aimed for home and independent use need to be developed. This pap...
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Trunk control and postural instability remain critical markers of functional status in Parkinson’s Disease (PD). As pharmacological and invasive neuro-stimulation interventions provide only limited benefits for trunk and postural control, exercise-based interventions may provide the only effective path to improving functional outcomes for balance i...
Joint Range of Motion (ROM) can be measured through a variety of methods including the use of sophisticated devices such as goniometers and non-intrusive three-dimensional (3D) sensor devices such as motion capture systems. The Microsoft Kinect has been proposed as an affordable motion capture device as an alternative to goniometers. However, due t...
Citations
... On the other hand, while strokes typically impact both extremities on one side of the body, the process of recovering or improving upper limb function is inherently more intricate compared to that of the lower limb. (Mandeljc et al. 2022). Observational studies reveal that 85% of stroke patients exhibit a reduction in upper limb function. ...
... Observational studies reveal that 85% of stroke patients exhibit a reduction in upper limb function. (Mandeljc et al. 2022) and up to 87% of stroke patients are reported to experience hand or upper limb weakness. (Choukou et al. 2021). ...
This study investigates the influence of immersive virtual reality environments and gamification on the classification of imaginary motor (MI) signals and the associated increase in energy in the motor cortex region for neurorehabilitation purposes. Two immersive virtual environments, indoor and outdoor, were selected, each with gamified and non-gamified scenarios. Event-Related Desynchronization (ERD) data underwent analyses to determine if there were significant differences in ERD levels between distinct age groups and whether Fully Immersive Virtual Reality (FIVR) environments induced notable energy increases.
The initial analysis found no significant energy changes between age groups under constant environmental conditions. In the second analysis, FIVR environments did not lead to a statistically significant increase in cortical energy for the 21–24 age group (Group I). However, a notable difference in cortical energy increase was identified between gamified and non-gamified environments within the 32–43 age group (Group II).
The study also explored the impact of environmental factors on MI signal classification using four deep learning algorithms. The Recurrent Neural Network (RNN) classifier exhibited the highest performance, with an average accuracy of 86.83%. Signals recorded indoors showed higher average classification performance, with a significant difference observed among age groups. Group I participants performed better in non-gamified environments (88.8%), while Group II achieved high performance indoors, especially in the gamified scenario (93.6%). Overall, the research underscores the potential of immersive virtual environments and gamification in enhancing MI signal classification and cortical energy increase, with age and environmental factors influencing the outcomes.
... One of the most common groups of these devices is Exoskeletons, such as M3ROB which is a robotic platform for wrist and hand [7], a lightweight exoskeleton based on hand kinematic model [1], an exoskeleton for wrist-finger [8], a three-degrees of freedom exoskeleton [9], an exoskeleton for the thumb, index, middle and ring fingers [10], FlexoHand [11], a passive exoskeleton for wrist and forearm [12], a wrist exoskeleton [13], HandMate [14], a cable-driven exoskeleton [15], and a hand exoskeleton with series elastic actuation [16]. A wide range of these devices has been created just for fingers such as a finger exoskeleton [17], a linkage finger exoskeleton [18], a magnetic-force-based for paralyzed fingers [19], a portable hand rehabilitation finger [20] and a finger extensor [21]. ...
... Therefore, a rehabilitation device that can safely provide passive exercises is desirable. To address these issues, various wearable and rehabilitation devices that support exercise and nursing care have been actively researched and developed [3][4][5][6][7][8][9][10][11]. Joints such as the upper limbs and legs were effectively exercised utilizing these devices. ...
... Joints such as the upper limbs and legs were effectively exercised utilizing these devices. However, from reference [3][4][5], previous rehabilitation devices for the upper limbs do not have flexible nursing care have been actively researched and developed [3][4][5][6][7][8][9][10][11]. Joints such as the upper limbs and legs were effectively exercised utilizing these devices. ...
... Based on Equations (4) to (9), the bending angle β of the HP-EFPA was calculated. Figure 25 compares the bending angles between the calculated and experimental results. ...
Rehabilitation devices for passive exercise have been actively researched and developed in accordance with Japan’s aging society. A previous study proposed and tested an extension-type flexible pneumatic actuator (EFPA) with reinforced stiffness that could achieve passive exercise in patients. In addition, a rehabilitation device for shoulder joints with an embedded controller and small valves was proposed and tested. Joints such as the shoulder and scapula were subjected to passive exercise utilizing the tested device. However, it is difficult for patients with contractions to perform the same exercise because the reinforced EFPA can buckle. Here, to realize an EFPA with a higher stiffness, a flexible actuator in the shape of a hexagonal pyramid is proposed and tested. The hexagonal pyramid shape of a flexible actuator has a high stiffness in the direction of motion and flexibility in other directions; hereafter, this characteristic is called anisotropic stiffness. The characteristics of the hexagonal pyramid shape of the EFPA are described and compared with those of a previously reinforced EFPA. An analytical model was proposed to predict and design the shape of the hexagonal pyramid EFPA. The validity of the model is also described.
... ADLs describe the fundamental daily activities that individuals can perform to maintain their quality of life. Rehabilitation is vital in treating post-stroke disabilities [3]. It involves a multidisciplinary team that can include doctors, physiotherapists, and healthcare assistants who play a vital role in the poststroke rehabilitation process. ...
... Initial clinical studies in rehabilitation robotics were performed using the MIT-MANUS robotic arm developed by MIT to investigate the effectiveness of target-based robotic-assisted movements [7]. However, many studies related to the post-stroke robotic rehabilitation of the upper limb, such as those involving MIT-MANUS [15] and GEN-TLE/S [16], focused primarily on arm joints, including the shoulder and elbow, rather than the hand and the finger joints [3]. As a result, the therapeutic exercises for some of these devices did not include the finger movements necessary to achieve pinching and grasping. ...
The preliminary test results of a novel robotic hand rehabilitation device aimed at treatment for the loss of motor abilities in the fingers and thumb due to stroke are presented. This device has been developed in collaboration with physiotherapists who regularly treat individuals who have suffered from a stroke. The device was tested on healthy adults to ensure comfort, user accessibility, and repeatability for various hand sizes in preparation for obtaining permission from regulatory bodies and implementing the design in a full clinical trial. Trials were conducted with 52 healthy individuals ranging in age from 19 to 93 with an average age of 58. A comfort survey and force data ANOVA were performed to measure hand motions and ensure the repeatability and accessibility of the system. Readings from the force sensor (p < 0.05) showed no significant difference between repetitions for each participant. All subjects considered the device comfortable. The device scored a mean comfort value of 8.5/10 on all comfort surveys and received the approval of all physiotherapists involved. The device has satisfied all design specifications, and the positive results of the participants suggest that it can be considered safe and reliable. It can therefore be moved forward for clinical trials with post-stroke users.
... Mandeljc et al. [5], designed a robotic device for stroke patients' wrist and finger rehabilitation. Their device is, in essence, an exoskeleton. ...
... Tele-rehabilitation device designed by Mandeljc et al.,[5]. ...
Hand fine motor functions may be impaired by various conditions, from injury to neurodegenerative diseases. Previously, we developed a prototype called Rehapiano that used load cells to measure the force exerted by the individual fingers. Rehapiano could distinguish between Parkinson’s patients and healthy individuals by analysing the finger tremors. Based on the experiences with the prototype and consultations with experts, we developed a more advanced prototype, Rehabimano. We show here how we improved the ergonomics and electronics. In addition, we have performed experimental validation of the device and confirmed its ability to detect and measure frequencies of tremors. These results are a stepping stone for consecutive software development and pre-clinical trials.
... This paper describes the design of a robotic device for post-stroke wrist and finger rehabilitation and evaluates the movement it can perform. Deviations from the baseline trajectory between measurement protocols and the root-mean-square deviation (RMSD) values indicate that the motion of the hand, imposed by the developed device, is comparable to the unconstrained motion of the healthy subjects, especially when moving into the extension, opening the hand [1]. ...
Robotic technology designed to assist rehabilitation can potentially increase the efficiency of and accessibility to therapy by assisting therapists in providing consistent training for extended periods of time and collecting data to assess progress [...]
BACKGROUND
Assistive technology is often incorporated into rehabilitation and support for those impacted by upper limb impairments. When powered, these devices provide additional force to the joints of users with muscle weakness. Actuated devices allow dynamic movement compared to splints, therefore improving the ability to complete activities of daily living. However, these devices are not often prescribed and are underrepresented in research and clinical settings.
OBJECTIVE
This review examined the existing literature on devices developed to support hand and wrist functionality in daily activities. Focusing on active, powered, and actuated devices, to gain a clearer understanding of the current limitations in their design and prescription.
METHODOLOGY
The scoping review was conducted using the PRISMA-ScR guidelines. A systematic search was done on MEDLINE, EMBASE, Scopus, Web of Science, and NHS the Knowledge Network from inception to May 2023. Articles were included if the device was portable; supported the hands and wrist actively using an actuator; and could be used for assistive living during or post-rehabilitation period.
FINDINGS
A total of 135 studies were included in the analysis of which 34 were clinical trials. The design and control methods of 121 devices were analyzed. Electrical stimulation and direct mechanical transmission were popular actuation methods. Electromyography (EMG) and joint movement detection were highly used control methods to translate user intentions to device actuation. A total of 226 validation methods were reported, of which 44% were clinically validated. Studies were often not conducted in operational environments with 69% at technology readiness levels ≤ 6, indicating that further development and testing is required.
CONCLUSION
The existing literature on hand and wrist exoskeletons presents large variations in validation methods and technical requirements for user-specific characteristics. This suggests a need for well-defined testing protocols and refined reporting of device designs. This would improve the significance of clinical outcomes and new assistive technology.
Electromyography (EMG) is a diagnostic technique that measures the electrical activity generated by skeletal muscles. Utilizing electrodes placed either on the skin (surface EMG) or inserted directly into the muscle(intramuscular EMG), it detects electrical signals produced during muscle contractions. EMG is widely employed in clinical and research settings to assess muscle function, diagnose neuromuscular disorders,and guide rehabilitation therapy. Over the years, EMG has evolved from a basic measurement tool into an essential technology within clinical and research environments, propelled by advances in recording techniques and digital innovations. The integration of wearable technology and artificial intelligence (AI) has significantly expanded its applications, particularly in rehabilitation and sports science. By capturing muscle electrical activity through surface or intramuscular electrodes, EMG benefits from enhanced signal processing that improves accuracy and data analysis. Despite challenges such as signal interference and the complexities of movement patterns—especially in wrist and hand rehabilitation—EMG combined with robotic systems offers real-time feedback for precise and personalized therapy. However, obstacles like cost, complexity, and variability among patients still remain. Future advancements aim to make EMG more accessible and to integrate AI for tailored rehabilitation strategies, alongside improvements in sensors and wireless communication to enhance reliability and performance. This review explores various facets of EMG,from its fundamental principles to its application in detecting disrupted wrist and hand movements through robotic approaches. It provides a comprehensive analysis of EMG’s historical and technological evolution, recent innovations like AI and wearable devices, and its extensive applications in rehabilitation and sports science. Detailed case studies illustrate its effectiveness in areas such as stroke recovery and spinal cord injury rehabilitation. Additionally, the review addresses challenges like technical limitations and patient variability while emphasizing the integration of EMG with robotic systems for personalized therapy. It also discusses the significance of real-time feedback, future enhancements in AI and sensor technology, and the pressing need for more affordable, user-friendly solutions to improve therapeutic outcomes.
