Posts Tagged Kinematics.

[ARTICLE] Determining the Accuracy of Oculus Touch Controllers for Motor Rehabilitation Applications Using Quantifiable Upper Limb Kinematics: Validation Study – Full Text

ABSTRACT

Background: As commercial motion tracking technology becomes more readily available, it is necessary to evaluate the accuracy of these systems before using them for biomechanical and motor rehabilitation applications.

Objective: This study aimed to evaluate the relative position accuracy of the Oculus Touch controllers in a 2.4 x 2.4 m play-space.

Methods: Static data samples (n=180) were acquired from the Oculus Touch controllers at step sizes ranging from 5 to 500 mm along 16 different points on the play-space floor with graph paper in the x (width), y (height), and z (depth) directions. The data were compared with reference values using measurements from digital calipers, accurate to 0.01 mm; physical blocks, for which heights were confirmed with digital calipers; and for larger step sizes (300 and 500 mm), a ruler with hatch marks to millimeter units.

Results: It was found that the maximum position accuracy error of the system was 3.5 ± 2.5 mm at the largest step size of 500 mm along the z-axis. When normalized to step size, the largest error found was 12.7 ± 9.9% at the smallest step size in the y-axis at 6.23 mm. When the step size was <10 mm in any direction, the relative position accuracy increased considerably to above 2% (approximately 2 mm at maximum). An average noise value of 0.036 mm was determined. A comparison of these values to cited visual, goniometric, and proprioceptive resolutions concludes that this system is viable for tracking upper-limb movements for biomechanical and rehabilitation applications. The accuracy of the system was also compared with accuracy values from previous studies using other commercially available devices and a multicamera, marker-based professional motion tracking system.

Conclusions: The study found that the linear position accuracy of the Oculus Touch controllers was within an agreeable range for measuring human kinematics in rehabilitative upper-limb exercise protocols. Further testing is required to ascertain acceptable repeatability in multiple sessions and rotational accuracy.

Introduction

Current gaming and virtual reality platforms [1] that use motion-controlled interfaces offer an affordable and accessible method of tracking human kinematics. However, given that consumer-grade platforms are originally intended for playing video games and to immerse players in virtual environments, their tracking performance should be evaluated before they are employed as tools for biomechanical or clinical analysis [2]. Previously tested rehabilitation protocols using commercial gaming technology such as Wii Motes (Nintendo Co, Ltd, Kyoto, Japan) to provide positional feedback for trunk compensation [3] or a Kinect (Microsoft Corporation, Redmond, United States) to measure range and speed of motion for upper-limb exercises [4,5] have shown potential to be used as rehabilitation tools that could provide quantifiable changes in clients’ kinematic motor abilities to therapists. Other studies using accelerometers to track patterns in functional upper-limb movements were able to capture differences similar to those measured by clinical scales [6] and found benefits from objective quantitative evaluations of changes in motor ability during therapy regimens, which can be collected from in-game progress reports [7]. In addition, success has been found in translating kinematic upper-limb metrics to clinical Fugl-Meyer scoring [8] and in detecting exercise repetitions via kinematic monitoring for telerehabilitation and at-home programs [9]. Current clinical assessments for upper-limb motor function, such as the Fugl-Meyer Assessment and Wolf Motor Function Test, only provide low-resolution point-scores rated qualitatively by therapists, and kinematic analysis of upper-limb motion has been reported to be a useful addition to these clinical assessments [10]. When measuring range of motion in a clinical setting, the goniometer is considered a gold-standard clinical measurement tool used by therapists [11]. However, only static joint angles can be measured, and typically with some visual estimation and multiple testers [12].

One of the latest (released December 2016) devices to be developed for interacting with virtual environments is the Oculus Touch (Oculus VR, LLC, Menlo Park, CA, United States) controller set. The controllers are peripheral accessories of the Oculus Rift virtual reality headset and are employed to track users’ hand movements. Their tracking system employs a proprietary algorithm that collects data from infrared sensors via constellation tracking [13] and inertial measurement units (IMUs). Given that the controllers are wireless, lightweight, low-cost devices that can be used to track a user’s hand position and orientation in 3-dimensional (3D) space, they could have the potential to be employed in rehabilitative and biomechanical motion-tracking applications. At the time of this study, there was no sufficient information about the tracking performance of the controllers provided by the manufacturer, and there is currently a lack of scientific papers employing a systematic approach to test their potential application as tools for motion-tracking data capture. As a result, in this study, we evaluated the tracking accuracy of the Oculus Touch controllers to present a preliminary evaluation that could be informative to the biomechanical and rehabilitation research community. The specific aim of the experiment was to quantify the relative positional accuracy of the Oculus Touch controllers in 3 spatial dimensions. As the controllers are intended for hand-held motion control, the evaluation setup was centered around the movement size for standing/sitting upper-limb reaching tasks.

Methods

Technical Setup

An Oculus Touch controller (Figure 1), 2 Oculus Sensors, an Oculus Rift headset, and a computer running Windows 10 (Microsoft Corporation) were employed in this study.

A custom computer application was developed in Unity 2017 (Unity Technologies, San Francisco, United States) to capture and log the controller’s position during the experiment. The data capture was performed at the headset’s native frequency of approximately 90 Hz , using the Unity OVR Plugin package to access controller data. The virtual environment was set up over a 2.4 m x 2.4 m play-space in the x-z plane to be within the recommended manufacturer play area. This space consists of 16 commercial 600 mm square force/torque plates professionally installed on a subfloor of auto-levelling epoxy and flat to within 0.5 mm (Figure 2). The y-axis was only bounded by the camera sensors’ field of view limitations.

To ensure consistency, the Oculus Sensors were placed on the floor at 0.3 m along the front edge of the space and 1.2 m apart, equidistant from the centre line, for the entire experiment. The sensor heads were manually leveled and visually aligned to have parallel, front-facing fields of views. Both the sensors and controllers maintained an initial y-position of 0 at the floor—this would be equivalent to placing the sensors at table height and the controllers at hand height.

All measurements were taken by securing the right-hand Oculus Touch controller to a flat L-shaped jig (Figure 2) and resting it on the floor for 5 seconds. Initial calibration of floor height and play-space size and orientation was done through the official commercial Oculus setup client.

Figure 1. The right-side Oculus Touch controller. Left: front view. Right: top-down view.

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Continue —>  JBME – Determining the Accuracy of Oculus Touch Controllers for Motor Rehabilitation Applications Using Quantifiable Upper Limb Kinematics: Validation Study | Shum | JMIR Biomedical Engineering

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[Abstract] Self-efficacy and Reach Performance in Individuals With Mild Motor Impairment Due to Stroke

Background: Persistent deficits in arm function are common after stroke. An improved understanding of the factors that contribute to the performance of skilled arm movements is needed. One such factor may be self-efficacy (SE).

Objective: To determine the level of SE for skilled, goal-directed reach actions in individuals with mild motor impairment after stroke and whether SE for reach performance correlated with actual reach performance.

Methods: A total of 20 individuals with chronic stroke (months poststroke: mean 58.1 ± 38.8) and mild motor impairment (upper-extremity Fugl-Meyer [FM] motor score: mean 53.2, range 39 to 66) and 6 age-matched controls reached to targets presented in 2 directions (ipsilateral, contralateral). Prior to each block (24 reach trials), individuals rated their confidence on reaching to targets accurately and quickly on a scale that ranged from 0 (not very confident) to 10 (very confident).

Results: Overall reach performance was slower and less accurate in the more-affected arm compared with both the less-affected arm and controls. SE for both reach speed and reach accuracy was lower for the more-affected arm compared with the less-affected arm. For reaches with the more-affected arm, SE for reach speed and age significantly predicted movement time to ipsilateral targets (R2 = 0.352), whereas SE for reach accuracy and FM motor score significantly predicted end point error to contralateral targets (R2 = 0.291).

Conclusions: SE relates to measures of reach control and may serve as a target for interventions to improve proximal arm control after stroke.

via Self-efficacy and Reach Performance in Individuals With Mild Motor Impairment Due to Stroke – Jill Campbell Stewart, Rebecca Lewthwaite, Janelle Rocktashel, Carolee J. Winstein, 2019

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[ARTICLE] Physiological and kinematic effects of a soft exosuit on arm movements – Full Text

Abstract

Background

Soft wearable robots (exosuits), being lightweight, ergonomic and low power-demanding, are attractive for a variety of applications, ranging from strength augmentation in industrial scenarios, to medical assistance for people with motor impairments. Understanding how these devices affect the physiology and mechanics of human movements is fundamental for quantifying their benefits and drawbacks, assessing their suitability for different applications and guiding a continuous design refinement.

Methods

We present a novel wearable exosuit for assistance/augmentation of the elbow and introduce a controller that compensates for gravitational forces acting on the limb while allowing the suit to cooperatively move with its wearer. Eight healthy subjects wore the exosuit and performed elbow movements in two conditions: with assistance from the device (powered) and without assistance (unpowered). The test included a dynamic task, to evaluate the impact of the assistance on the kinematics and dynamics of human movement, and an isometric task, to assess its influence on the onset of muscular fatigue.

Results

Powered movements showed a low but significant degradation in accuracy and smoothness when compared to the unpowered ones. The degradation in kinematics was accompanied by an average reduction of 59.20±5.58% (mean ± standard error) of the biological torque and 64.8±7.66% drop in muscular effort when the exosuit assisted its wearer. Furthermore, an analysis of the electromyographic signals of the biceps brachii during the isometric task revealed that the exosuit delays the onset of muscular fatigue.

Conclusions

The study examined the effects of an exosuit on the characteristics of human movements. The suit supports most of the power needed to move and reduces the effort that the subject needs to exert to counteract gravity in a static posture, delaying the onset of muscular fatigue. We interpret the decline in kinematic performance as a technical limitation of the current device. This work suggests that a powered exosuit can be a good candidate for industrial and clinical applications, where task efficiency and hardware transparency are paramount.

Background

In the never-ending quest to push the boundaries of their motor performance, humans have designed a wealth of wearable robotic devices. In one of the earliest recorded attempts to do so, in 1967, Mosher aspired to create a symbiotic unit that would have the “…alacrity of man’s information and control system coupled with the machine’s power and ruggedness” [1]. His design of the Hardiman, although visionary, ran into fundamental technological limitations.

Advances in materials science, electronics and energy storage have since enabled an exponential growth of the field, with state-of-the-art exoskeletons arguably accomplishing Mosher’s vision [2]. Wearable robotic technology has been successful in augmenting human strength during locomotion [3], reducing the metabolic cost of human walking [45], restoring ambulatory capabilities to paraplegic patients [6], assisting in rehabilitating stroke patients [789], harvesting energy from human movements [10] and helping to study fundamental principles underlying human motor control [1112].

These feats were achieved with machines made of rigid links of metal and capable of accurately and precisely delivering high forces to their wearer. While this is undeniably an advantage, it comes at a cost: 1) a significant inertia, which affects both the kinematics of human movement and the power requirements of the device; 2) the need for the joints of the robot to be aligned with the biological joints [13], resulting in increased mechanical complexity and size [14]; 3) a strong cosmetic impact, shown to be linked with psychological health and well-being [15].

The recent introduction of soft materials to transmit forces and torques to the human body [16] has allowed to design wearable robotic devices on the other side of the spectrum: lightweight, low-profile and compliant machines that sacrifice accuracy and magnitude of assistance for the sake of portability and svelteness.

Soft exoskeletons, or exosuits, are clothing-like devices made of fabric or elastomers that wrap around a person’s limb and work in parallel with his/her muscles [1718]. Characteristic of exosuits is that they rely on the structural integrity of the human body to transfer reaction forces between body segments, rather than having their own frame, thus acting more like external muscles than an external skeleton. Their intrinsic compliance removes the need for alignment with the joints and their low-profile allows to wear them underneath everyday clothing.

Exosuits actively transmit power to the human body either using cables, moved by electric motors, or soft pneumatic actuators, embedded in the garment. The latter paradigm was probably among the first to be proposed [19] and has been explored to assist stroke patients during walking [20], to increase shoulder mobility in subjects with neuromuscular conditions [21], to help elbow movements [22] and for rehabilitation purposes to train and aid grasping [232425].

Cable-driven exosuits, instead, include a DC motor that transmits power to the suit using Bowden cables. This flexible transmission allows to locate the actuation stage where its additional weight has the least metabolic impact on its wearer. Using this paradigm to provide assistance to the lower limbs has resulted in unprecedented levels of walking economy in healthy subjects [26] and improved symmetry and efficiency of mobility in stroke patients [27]. Similar principles were used to provide active support to hip and knee extension, reducing activation of the gluteus maximus in sit-to-stand and stand-to-sit transitions [28].

Cable-driven exosuits seem to work particularly well for lower-limbs movements, where small bursts of well-timed assistance can have a big impact on the dynamics and metabolic cost of locomotion [29]. Yet, Park et al. have shown that they have the potential for assisting the upper-limbs in quasi-static movements too: using a tendon-driving mechanism, a textile interface and an elastic component they found a significant reduction in the activity of the deltoid muscle when supporting the weight of the arm [30].

Similar results were reported by Chiaradia et al., where a soft exosuit for the elbow was shown to reduce the activation of the biceps brachii muscle in dynamic movements [31], and by Khanh et al., where the same device was used to improve the range of motion of a patient suffering from bilateral brachial plexus injury [32].

While there is extensive work on the analysis of the effects of wearing a soft exosuit on the kinematics, energetics and muscular activation during walking [33], the authors are unaware of comparable studies on movements of the upper limbs, whose variety of volitional motions is fundamentally different from the rhythmic nature of walking.

Understanding how these devices affect the physiology and mechanics of human movements is fundamental for quantifying their benefits and drawbacks, assessing their suitability for different applications and guiding a continuous data-driven design refinement.

In this study we investigate the kinematic and physiological effects of wearing a cable-driven exosuit to support elbow movements. We hypothesize that the low inertia and soft nature of the exosuit will allow it to work in parallel with the user’s muscles, delaying the onset of fatigue while having little to no impact on movement kinematics.

We propose a variation of the design and controller presented in [3234] and introduce a controller that both detects the wearer’s intention, allowing the suit to quickly shadow the user’s movements, and compensates for gravitational forces acting on the limb, thus reducing the muscular effort required for holding a static posture. We collect kinematic, dynamic and myoelectric signals from subjects wearing the device, finding that the exosuit affects motion smoothness, significantly reduces muscular effort and delays the onset of fatigue. The analysis offers interesting insights on the viability of using this technology for human augmentation/assistance and medical purposes.

Methods

Exosuit design

An exosuit is a device consisting of a frame made of soft material that wraps around the human body and transmits forces to its wearer’s skeletal structure. In a cable-driven exosuit, artificial tendons are routed along a targeted joint and attached to anchor points on both of its sides. When the tendons are tensioned they deliver an assistive moment to the joint.

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Continue —>  Physiological and kinematic effects of a soft exosuit on arm movements | Journal of NeuroEngineering and Rehabilitation | Full Text

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[Abstract + References] Synergy-Based FES for Post-Stroke Rehabilitation of Upper-Limb Motor Functions

Abstract

Functional electrical stimulation (FES) is capable of activating muscles that are under-recruited in neurological diseases, such as stroke. Therefore, FES provides a promising technology for assisting upper-limb motor functions in rehabilitation following stroke. However, the full benefits of FES may be limited due to lack of a systematic approach to formulate the pattern of stimulation. Our preliminary work demonstrated that it is feasible to use muscle synergy to guide the generation of FES patterns.In this paper, we present a methodology of formulating FES patterns based on muscle synergies of a normal subject using a programmable multi-channel FES device. The effectiveness of the synergy-based FES was tested in two sets of experiments. In experiment one, the instantaneous effects of FES to improve movement kinematics were tested in three patients post ischemic stroke. Patients performed frontal reaching and lateral reaching tasks, which involved coordinated movements in the elbow and shoulder joints. The FES pattern was adjusted in amplitude and time profile for each subject in each task. In experiment two, a 5-day session of intervention using synergy-based FES was delivered to another three patients, in which patients performed task-oriented training in the same reaching movements in one-hour-per-day dose. The outcome of the short-term intervention was measured by changes in Fugl–Meyer scores and movement kinematics. Results on instantaneous effects showed that FES assistance was effective to increase the peak hand velocity in both or one of the tasks. In short-term intervention, evaluations prior to and post intervention showed improvements in both Fugl–Meyer scores and movement kinematics. The muscle synergy of patients also tended to evolve towards that of the normal subject. These results provide promising evidence of benefits using synergy-based FES for upper-limb rehabilitation following stroke. This is the first step towards a clinical protocol of applying FES as therapeutic intervention in stroke rehabilitation.

I. Introduction

Muscle activation during movement is commonly disrupted due to neural injuries from stroke. A major challenge for stroke rehabilitation is to re-establish the normal ways of muscle activation through a general restoration of motor control, otherwise impairments may be compensated by the motor system through a substitution strategy of task control [1]. In post-stroke intervention, new technologies such as neuromuscular electrical stimulation (NMES) or functional electrical stimulation (FES) offer advantages for non-invasively targeting specific groups of muscles [2]–[4] to restore the pattern of muscle activation. Nevertheless, their effectiveness is limited by lack of a systematic methodology to optimize the stimulation pattern, to implement the optimal strategy in clinical settings, and to design a protocol of training towards the goal of restoring motor functions. This pioneer study addresses these issues in clinical application with a non-invasive FES technology.

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53. W. H. Backes, W. H. Mess, V. van Kranen-Mastenbroek, and J. P. H. Reulen, “Somatosensory cortex responses to median nerve stimulation: fMRI effects of current amplitude and selective attention,” Clin. Neurophysiol., vol. 111, no. 10, pp. 1738–1744, Oct. 2000.

54. G. Francisco, “Electromyogram-triggered neuromuscular stimulation for improving the arm function of acute stroke survivors: A randomized pilot study,” Arch. Phys. Med. Rehabil., vol. 79, no. 5, pp. 570–575, May 1998.

55. S. K. Sabut, C. Sikdar, R. Kumar, and M. Mahadevappa, “Functional electrical stimulation of dorsiflexor muscle: Effects on dorsiflexor strength, plantarflexor spasticity, and motor recovery in stroke patients,” Neurorehabilitation, vol. 29, no. 4, pp. 393–400, 2011.

56. Y.-H. Wang, F. Meng, Y. Zhang, M.-Y. Xu, and S.-W. Yue, “Full-movement neuromuscular electrical stimulation improves plantar flexor spasticity and ankle active dorsiflexion in stroke patients: A randomized controlled study,” Clin. Rehabil., vol. 30, no. 6, pp. 577–586, Jun. 2016.

57. W. H. Chang and Y.-H. Kim, “Robot-assisted therapy in stroke rehabilitation,” J. Stroke, vol. 15, no. 3, p. 174, 2013.

58. H. G. Wu, Y. R. Miyamoto, L. N. G. Castro, B. P. Ölveczky, and M. A. Smith, “Temporal structure of motor variability is dynamically regulated and predicts motor learning ability,” Nature Neurosci., vol. 17, no. 2, pp. 312–321, Jan. 2014.

59. J. Frère and F. Hug, “Between-subject variability of muscle synergies during a complex motor skill,” Frontiers Comput. Neurosci., vol. 6, p. 99, Dec. 2012.

60. S. Muceli, A. T. Boye, A. d’Avella, and D. Farina, “Identifying representative synergy matrices for describing muscular activation patterns during multidirectional reaching in the horizontal plane,” J. Neurophysiol., vol. 103, no. 3, pp. 1532–1542, Mar. 2010.

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62. B. Cesqui, A. d’Avella, A. Portone, and F. Lacquaniti, “Catching a ball at the right time and place: Individual factors matter,” PLoS ONE, vol. 7, no. 2, p. e31770, Feb. 2012.

 

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[Abstract] Configuration Optimization of a Dual-Arm Rehabilitation Robot – IEEE Conference Publication

Abstract:

Robotic rehabilitation devices have gained high popularity in upper limb physical therapy for stroke patients. Dual-Arm rehabilitation robot system has advantages in achieving coordinated motions for the upper arm and forearm segments. In this paper, an efficient method for the design and evaluation of the kinematics of a dual-arm robot for upper limb rehabilitation, is presented. First, requirements for an upper limb rehabilitation robot are analyzed and candidate manipulator structures are presented. Then, workspace and manipulability, which are served as the criterion of the optimization configuration of a dual-arm rehabilitation robot, are analyzed. Thereafter, the optimal configuration is modeled and simulated to verify the method. Finally, simulation results are shown.

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[Abstract + References] Novel Assessment Measures of Upper-Limb Function in Pre and Poststroke Rehabilitation: A Pilot Study – IEEE Conference Publication

Abstract

Hand function assessment is essential for upper limb rehabilitation of stroke survivors. Conventional acquisition devices have inherent and restrictive difficulties for their clinical usage. Data gloves are limited for applications outside the medical environment, and motion tracking systems setup are time and personnel demanding. We propose a novel instrument designed as a replica of a glass, equipped with an omnidirectional vision system to capture hand images and an inertial measurement unit for movements kinematic data acquisition. Four stroke survivors were invited as volunteers in pre and post-treatment experiments for its evaluating. The exercise of drinking water from a glass was elected for the trails. Before treatment, subjects used their contralesional and ipsilateral hands to perform them. Two main functional features were found in the data analysis. There were differences between limbs in the grasping hand postures, mainly in the index and thumb abduction angle, and in the task timing. After treatment, two volunteers repeated the protocol with their contralesional hands. Changes in the features were observed, index and thumb abduction angles were greater in both cases, and tasks timing were altered in distinct ways. These preliminary results suggest the instrument can be used both in evaluation of hand functional deficit and rehabilitation progress. Improvements and future work are also presented.
1. R. L. Sacco, S. E. Kasner, J. P. Broderick, L. R. Caplan, A. Culebras, M. S. Elkind, M. G. George, A. D. Hamdan, R. T. Higashida, B. L. Hoh et al., “An updated definition of stroke for the 21st century: a statement for healthcare professionals from the american heart association/american stroke association”, Stroke, vol. 44, no. 7, pp. 2064-2089, 2013.

2. C. A. Doman, K. J. Waddell, R. R. Bailey, J. L. Moore, C. E. Lang, “Changes in upper-extremity functional capacity and daily performance during outpatient occupational therapy for people with stroke”, American Journal of Occupational Therapy, vol. 70, no. 3, pp. 7003290040pl-7003290040p11, 2016.

3. B. Brouwer, M. V. Sale, M. A. Nordstrom, “Asymmetry of motor cortex excitability during a simple motor task: relationships with handedness and manual performance”, Experimental Brain Research, vol. 138, no. 4, pp. 467-476, 2001.

4. J. Langan, P. van Donkelaar, “The influence of hand dominance on the response to a constraint-induced therapy program following stroke”, Neurorehabilitation and neural repair, vol. 22, no. 3, pp. 298-304, 2008.

5. H. I. Krebs, M. L. Aisen, B. T. Volpe, N. Hogan, “Quantization of continuous arm movements in humans with brain injury”, Proceedings of the National Academy of Sciences, vol. 96, no. 8, pp. 4645-4649, 1999.

6. B. Fisher, C. Winstein, M. Velicki, “Deficits in compensatory trajectory adjustments after unilateral sensorimotor stroke”, Experimental brain research, vol. 132, no. 3, pp. 328-344, 2000.

7. H. Sugarman, A. Avni, R. Nathan, A. Weisel-Eichler, J. Tiran, “Movement in the ipsilesional hand is segmented following unilateral brain damage”, Brain and cognition, vol. 48, no. 2-3, pp. 579-587, 2002.

8. D. A. Nowak, “The impact of stroke on the performance of grasping: usefulness of kinetic and kinematic motion analysis”, Neuroscience & Biobehavioral Reviews, vol. 32, no. 8, pp. 1439-1450, 2008.

9. M. Coluccini, E. S. Maini, C. Martelloni, G. Sgandurra, G. Cioni, “Kinematic characterization of functional reach to grasp in normal and in motor disabled children”, Gait & posture, vol. 25, no. 4, pp. 493-501, 2007.

10. E. Jaspers, H. Feys, H. Bruyninckx, J. Harlaar, G. Molenaers, K. Desloovere, “Upper limb kinematics: development and reliability of a clinical protocol for children”, Gait & posture, vol. 33, no. 2, pp. 279-285, 2011.

11. D. A. Nowak, J. Hermsdörfer, H. Topka, “Deficits of predictive grip force control during object manipulation in acute stroke”, Journal of neurology, vol. 250, no. 7, pp. 850-860, 2003.

12. R. W. Bohannon, “Adequacy of hand-grip dynamometry for characterizing upper limb strength after stroke”, Isokinetics and exercise science, vol. 12, no. 4, pp. 263-265, 2004.

13. H. Zhou, H. Hu, “Human motion tracking for rehabilitationâĂŤa survey”, Biomedical Signal Processing and Control, vol. 3, no. 1, pp. 1-18, 2008.

14. A. C. P. Rocha, E. Tudella, L. M. Pedro, V. C. R. Appel, L. G. P. da Silva, G. A. d. P. Caurin, “A novel device for grasping assessment during functional tasks: preliminary results”, Frontiers in bioengineering and biotechnology, vol. 4, pp. 16, 2016.

15. E. Taub, G. Uswatte, “Constraint-induced movement therapy: bridging from the primate laboratory to the stroke rehabilitation laboratory”, Journal of Rehabilitation Medicine-Supplements, vol. 41, pp. 34-40, 2003.

16. R. d. N. B. Marques, A. C. Magesto, R. E. Garcia, C. B. d. Oliveira, G. d. S. Matuti, “Efeitos da terapia por contensão induzida nas lesões encefálicas adquiridas”, Fisioterapia Brasil, vol. 17, no. 1, pp. f-30, 2016.

17. E. E. Butler, A. L. Ladd, L. E. LaMont, J. Rose, “Temporal-spatial parameters of the upper limb during a reach & grasp cycle for children”, Gait & posture, vol. 32, no. 3, pp. 301-306, 2010.

18. E. E. Butler, A. L. Ladd, S. A. Louie, L. E. LaMont, W. Wong, J. Rose, “Three-dimensional kinematics of the upper limb during a reach and grasp cycle for children”, Gait & posture, vol. 32, no. 1, pp. 72-77, 2010.

19. L. Gauthier, Structural brain changes produced by different motor therapies after stroke, 2011.

20. L. M. Pedro, G. A. de Paula Caurin, “Kinect evaluation for human body movement analysis”, Biomedical Robotics and Biomechatronics (BioRob) 2012 4th IEEE RAS & EMBS International Conference on, pp. 1856-1861, 2012.

21. A. Hussain, S. Balasubramanian, N. Roach, J. Klein, N. Jarrassé, M. Mace, A. David, S. Guy, E. Burdet, “Sitar: a system for independent task-oriented assessment and rehabilitation”, Journal of Rehabilitation and Assistive Technologies Engineering, vol. 4, pp. 2055668317729637, 2017.

22. L. R. L. Cardoso, M. N. Martelleto, P. M. Aguiar, E. Burdet, G. A. P. Caurin, L. M. Pedro, “Upper limb rehabilitation through bicycle controlling”, 24th International Congress of Mechanical Engineering, 2017.

23. M. N. Martelleto, P. M. Aguiar, E. Burdet, G. A. P. Caurin, R. V. Aroca, L. M. Pedro, “Instrumented module for investigation of contact forces for use in rehabilitation and assessment of bimanual functionalities”, 24th International Congress of Mechanical Engineering, 2017.

 

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[Abstract] Design and Development of a Robot Guided Rehabilitation Scheme for Upper Extremity Rehabilitation

Abstract

To rehabilitate individuals with impaired upper-limb function, we have designed and developed a robot guided rehabilitation scheme. A humanoid robot, NAO was used for this purpose. NAO has 25 degrees of freedom. With its sensors and actuators, it can walk forward and backward, can sit down and stand up, can wave his hand, can speak to the audience, can feel the touch sensation, and can recognize the person he is meeting. All these qualities have made NAO a perfect coach to guide the subjects to perform rehabilitation exercises. To demonstrate rehabilitation exercises with NAO, a library of recommended rehabilitation exercises involving shoulder (i.e., abduction/adduction, vertical flexion/extension, and internal/external rotation), and elbow (i.e., flexion/extension) joint movements was formed in Choregraphe (graphical programming interface). In experiments, NAO was maneuvered to instruct and demonstrate the exercises from the NRL. A complex ‘touch and play’ game was also developed where NAO plays with the subject that represents a multi-joint movement’s exercise. To develop the proposed tele-rehabilitation scheme, kinematic model of human upper-extremity was developed based modified Denavit-Hartenberg notations. A complete geometric solution was developed to find a unique inverse kinematic solution of human upper-extremity from the Kinect data. In tele-rehabilitation scheme, a therapist can remotely tele-operate the NAO in real-time to instruct and demonstrate subjects different arm movement exercises. Kinect sensor was used in this scheme to get tele-operator’s kinematics data. Experiments results reveals that NAO can be tele-operated successfully to instruct and demonstrate subjects to perform different arm movement exercises. A control algorithm was developed in MATLAB for the proposed robot guided supervised rehabilitation scheme. Experimental results show that the NAO and Kinect sensor can effectively be used to supervise and guide the subjects in performing active rehabilitation exercises for shoulder and elbow joint movements.

Recommended Citation
Assad-Uz-Zaman, Md, “Design and Development of a Robot Guided Rehabilitation Scheme for Upper Extremity Rehabilitation” (2017). Theses and Dissertations. 1578.
https://dc.uwm.edu/etd/1578

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[Abstract] Kinematic analysis and control for upper limb robotic rehabilitation system – IEEE Conference Publication

Abstract

Present physical rehabilitation practice implies one-to-one therapist — patient interactions. This leads to shortage of therapists and high costs for patient or healthcare insurance systems. Along with Prokinetic Rehabilitation Clinic, we proposed a new intelligent, adaptive robotic system (RAPMES), which can provide the rehabilitation protocols, defined by a therapist, for the wrist and elbow of upper limb, considering the patient reactions and based on real-time feedback. RAPMES is a passive rehabilitation robotic system (RRS) with 3 degrees of freedom, and assists the rehabilitation process for elbow, forearm and wrist movements. Computation of the kinematic model for the RAPMES robotic device is required in order to determine the parameters associated with the mechanical joints, so that the experimental model executes certain trajectories in space. In this paper, we will present both forward and inverse kinematics determined for the experimental model. The kinematic model was implemented in Matlab environment, and we present a series of simulations, conducted in order to validate the proposed kinematic model. Then, we impose the functional movements (determined using the real-time video motion analysis system, as polynomial movement functions) as input to the kinematic model, and we present a series of simulations and results. The RAPMES control algorithm includes the kinematic model, and uses the polynomial movement functions as control input.
Date of Conference: 28-31 May 2018

 

I. Introduction

Statistics shows that, at European Union level, the upper limb is second common body part injured, as a result of unintentional physical injury [1]. Also, one can note the shortage of therapists and high costs for patient or healthcare insurance systems. Current development in robotics may offer a solution for this problem [2], allowing the creation of robotic devices to support the rehabilitation process, in a supervised or unsupervised way, in physiotherapy clinics or at home. In this context, we proposed RAPMES, a new intelligent, adaptive robotic system, which can provide the rehabilitation protocols, defined by a therapist, for the wrist and elbow of upper limb, considering the patient reactions and based on real-time feedback. RAPMES robotic system is designed on an ongoing research project, which implies several stages of development. In a first stage, we conducted a study involving therapists, the personnel and devices existent in a physiotherapy clinic. The role of this study was to determine the requirements for the robotic device, and to reveal the specific therapeutic needs of patients with rehabilitation indications at wrist and elbow level. On a second stage, we used a real-time video motion analysis system, to determine and understand specific functional movements frequently made with the dominant upper limb, by healthy persons. One of our research objectives is to include these movements as a part of RAPMES control algorithm, as they may offer a better rehabilitation of the upper limb, for specific moves. Next, we designed the robotic device, based on findings described above, and realized an experimental model of the robotic device.

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[Abstract] A Portable Passive Rehabilitation Robot for Upper-Extremity Functional Resistance Training

Abstract:

Objective: Loss of arm function is common in individuals with neurological damage, such as stroke or cerebral palsy. Robotic devices that address muscle strength deficits in a task-specific manner can assist in the recovery of arm function; however, current devices are typically large, bulky, and expensive to be routinely used in the clinic or at home. This study sought to address this issue by developing a portable planar passive rehabilitation robot, PaRRo. Methods: We designed PaRRo with a mechanical layout that incorporated kinematic redundancies to generate forces that directly oppose the user’s movement. Cost-efficient eddy current brakes were used to provide scalable resistances. The lengths of the robot’s linkages were optimized to have a reasonably large workspace for human planar reaching. We then performed theoretical analysis of the robot’s resistive force generating capacity and steerable workspace using MATLAB simulations. We also validated the device by having a subject move the end-effector along different paths at a set velocity using a metronome while simultaneously collecting surface electromyography (EMG) and end-effector forces felt by the user. Results: Results from simulation experiments indicated that the robot was capable of producing sufficient end-effector forces for functional resistance training. We also found the endpoint forces from the user were similar to the theoretical forces expected at any direction of motion. EMG results indicated that the device was capable of providing adjustable resistances based on subjects’ ability levels, as the muscle activation levels scaled with increasing magnet exposures. Conclusion: These results indicate that PaRRo is a feasible approach to provide functional resistance training to the muscles along the upper extremity. Significance: The proposed robotic device could provide a technological breakthrough that will make rehabilitation robots accessible for small outpatient rehabilitation centers and in-home therapy.

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[Conference paper] Kinematic Design of a Parallel Robot for Elbow and Wrist Rehabilitation|Abstract+References

Abstract

This paper presents the kinematics of modular a parallel robot for post-stroke rehabilitation of elbow and wrist. The targeted motions for rehabilitation are: elbow flexion, pronation/supination, flexion/extension and adduction/abduction (radial/ulnar deviation) of the wrist. The kinematic structure of the robotic system is presented starting from general considerations concerning the rehabilitation protocol of the upper limb. Its kinematics is developed and simulation results are presented for a proposed training exercise.

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