Posts Tagged ROM
[ARTICLE] Gamification in a Physical Rehabilitation Setting: Developing a Proprioceptive Training Exercise for a Wrist Robot – Full Text
Proprioception, the sense of body awareness, is essential for normal motor function. Proprioceptive deficits are common in neurological conditions [Coupar et al. 2012; Konczak et al. 2009]. Such deficits cause a decline in precision of goal-directed movements, and altered postural and spinal reflexes resulting in balance and gait problems [Rothwell et al. 1982]. Proprioceptive training is an intervention aiming to improve proprioceptive function [Aman et al. 2015]. Previous work has established the efficacy of a robot-aided proprioceptive training using WristBot [Elangovan et al. 2017, 2018, 2019]. The WristBot (Figure 1. Left) is a three degrees-of-freedom (3-DoF) exoskeleton robot that allows full range of motion (ROM), delivers precise haptic, position, and velocity stimuli at the wrist, and accurately encodes wrist position across time. Additional details about the WristBot can found in [Cappello et al. 2015].
Nevertheless, while the WristBot has demonstrated its efficacy, it shares a limitation that is often encountered in rehabilitation settings. In a clinical setting, patients are often required to perform task-specific and repetitive movements [Kwakkel et al. 1999]. Initial patient enthusiasm to complete such activities rapidly declines as a result of the monotonous nature of movements. Patient engagement can be improved by complementing therapy with a virtual environment (VE). Prior research has shown that users have favored exercises complemented with a VE rather than conventional approaches [Hoffman et al. 2014]. Thus, our project objective is to turn these tedious movements into an interactive VE experience.
Gamification process accounted for two key considerations: (1) the game should foster patient motivation and attention (2) and be clinically meaningful. To address these objectives, we reviewed the literature on game development [Bond 2014; Fullerton 2018] and identified four essential components: (1) Variability, (2) Feedback, (3) Rewards, and (4) a Compelling Purpose. The user will be gradually exposed to increasing levels of difficulty, which will likely reduce user frustrations. The user will receive meaningful feedback on concurrent metrics (e.g., Optimal ROM), as well as on previous treatment sessions. During game progress, the user will be alerted about deviations from the target movement requirements. Achievement badges will be rewarded to the user upon reaching therapy milestones, such as target ROM. Lastly, to encourage game completion, we establish an interesting backstory and a meaningful character arc for our virtual avatars. The developed game will be adaptable based on the user’s current clinical status, thus, making the game clinically meaningful. The clinician will have the ability to prescribe exercises based on user needs such as 1 DoF vs 3 DoF movements, continuous vs discrete movements, and strength training vs mobility training. WristBot will provide supportive forces aiding the user to achieve therapy milestones.
Gamified exercise is being developed using the Unity Game Engine, Python and libraries which interface with the WristBot. The game closely resembles an endless runner type game (Figure 1. Right) and utilizes the WrsitBot’s 3-DoF functionality to interact with the VE. Wrist flexion, extension, and abduction can be used to traverse their environment. The remaining 3 movements will allow interactions with their VE in unique ways, such as opening/closing doors, crouching, and pulling levers. In the VE, coins are strategically placed to maximize and improve the use of available ROM. Upon contact with either a wall or obstacle, visual feedback will be provided in the form of avatar damage and coin deduction. Consequently, users achieve improved mobility.
In Python, the connection between Unity and the WristBot library is managed through the use of a local WebSocket, a protocol for two-way communication over a single Transmission Control Protocol (TCP) connection [Fette and Melnikov 2011]. Through the WebSocket, reciprocal data are transferred between the WristBot and Unity. For example, wrist kinematic data will be streamed to the game while game progress is being relayed to the WristBot library. Game progress data will be utilized to compute and deliver haptic feedback to the user. Haptic feedback provided in the form of haptic assistance will aid users to improve their available ROM, while haptic resistance will improve muscle strength within the desired ROM. The clinical motive of the game is to transition the user from use of haptic assistance to resistance during game play. WristBot will adapt haptic feedback based on time spent and progress achieved in game play.
Usability testing will be conducted to ensure proper game usage by the clinical population and healthcare professionals. Specifically, the usability testing will evaluate areas such as 1) ease of game play, 2) game efficiency, and 3) user engagement. We will test the assumptions in each of these areas are accurately depicted in game development and met during game play. For example, we expect online visual feedback of deviations from target to help user focus on achieving the movement requirements. The users will be asked to verify the benefits of visual feedback in modifying their movements. Similarly, other assumptions such as performance badges and coins as rewards, and increase in difficulty levels will be evaluated. A common pitfall of usability studies involving physical rehabilitation setting is not recruiting from the representative population, most notably elderly population [Laver et al. 2017] as age has been shown to interfere with interactions in VE [Meldrum et al. 2012]. Therefore, to ensure our game is intuitive, we will recruit representative users from our patient populations.
This project was supported by National Science Foundation Partnerships For Innovation Technology Translation Award to Jürgen Konczak (1919036). Christopher Curry was supported by National Research Trainee-Understanding the Brain: Graduate Training Program in Sensory Science: Optimizing the Information Available for Mind and Brain (1734815).
- Joshua E Aman, Naveen Elangovan, I Yeh, Jürgen Konczak, et al. 2015. The effectiveness of proprioceptive training for improving motor function: a systematic review. Frontiers in human neuroscience 8 (2015), 1075.
- Jeremy Gibson Bond. 2014. Introduction to Game Design, Prototyping, and Development: From Concept to Playable Game with Unity and C. Addison-Wesley Professional.
- Leonardo Cappello, Naveen Elangovan, Sara Contu, Sanaz Khosravani, Jürgen Konczak, and Lorenzo Masia. 2015. Robot-aided assessment of wrist proprioception. Frontiers in human neuroscience 9 (2015), 198.
- Fiona Coupar, Alex Pollock, Phil Rowe, Christopher Weir, and Peter Langhorne. 2012. Predictors of upper limb recovery after stroke: a systematic review and meta-analysis. Clinical rehabilitation 26, 4 (2012), 291–313.
- Naveen Elangovan, Leonardo Cappello, Lorenzo Masia, Joshua Aman, and Jürgen Konczak. 2017. A robot-aided visuo-motor training that improves proprioception and spatial accuracy of untrained movement. Scientific reports 7, 1 (2017), 17054.
- Naveen Elangovan, Paul Tuite, and Jürgen Konczak. 2018. Somatosensory training improves proprioception and untrained motor function in Parkinson’s disease. Frontiers in neurology 9(2018), 1053.
- Naveen Elangovan, I-Ling Yeh, Jessica Holst-Wolf, and Jürgen Konczak. 2019. A robot-assisted sensorimotor training program can improve proprioception and motor function in stroke survivors. In 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR). IEEE, 660–664.
- I. Fette and A. Melnikov. 2011. The WebSocket Protocol. Technical Report.
- Tracy Fullerton. 2018. Game design workshop: a playcentric approach to creating innovative games. AK Peters/CRC Press.
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[Abstract] Target-focused exercise regime to improve patient compliance and range of motion in the stiff hand
- Stiff hands are more commonly seen in the clinics.
- The management of stiff hand is often complicated.
- Target-focused exercise regime is fast and simple technique for managing stiff hands.
- Target-focused exercise regime improves compliance and ROM with ease and comfort.
WalkAide: Helping You Get a Leg Up on Foot Drop
|WalkAide is a class II, FDA cleared medical device, designed to improve walking ability in people experiencing foot drop caused by upper motor neuron injuries or conditions such as:
Foot Drop or Dropped Foot is a condition caused by weakness or paralysis of the muscles involved in lifting the front part of the foot, which causes a person to drag the toe of the shoe on the ground or slap the foot on the floor.
Foot drop (also known as drop foot) may result from damage to the central nervous system such as stroke, spinal cord injury, traumatic brain injury, cerebral palsy and multiple sclerosis. The WalkAide is designed to assist with the ability to lift the foot for those individuals who have suffered an injury to their central nervous system. The WalkAide is not designed to work with people who have damage to the lower motor neurons/peripheral nerves.
WalkAide vs. AFO
Traditionally, foot drop is treated with bracing using an ankle foot orthosis (AFO). The passive treatement offered by AFOs do not promote active use of neuromuscular systems and also limits ankle range of motion. In addition, AFOs can be uncomfortable, bulky, and, if poorly fitted, produce areas of pressure and tissue breakdown. The WalkAide may replace the traditional AFO to re-engage a person’s existing nerve pathways and muscles. Using the WalkAide, in most cases, frees the patient from AFO restrictions.
The recruitment of existing muscles results in reduction of atrophy and walking fatigue – a common side effect of foot bracing. WalkAide users have the freedom to walk with or without footwear, up and down the stairs, and even sidestep.
Advanced Technology; Easy to Use
Invented by a team of researchers at the University of Alberta, WalkAide uses functional electrical stimulation (FES) to restore typical nerve-to-muscle signals in the leg and foot, effectively lifting the foot at the appropriate time. The resulting movement is a smoother, more natural and safer stepping motion. It may allow faster walking for longer distances with less fatigue. In fact, many people who try WalkAide experience immediate and substantial improvement in their walking ability, which increases their mobility, functionality, and overall independence.
A sophisticated medical device, WalkAide uses advanced tilt sensor technology to analyze the movement of your leg. This tilt sensor adjust the timing of stimulation for every step. The system sends electrical signals or stimulation to the peroneal nerve, which controls movement in your ankle and foot. These gentle electrical impulses activate the muscles to raise your foot at the appropriate time during the step cycle.
Although highly-advanced, WalkAide is surprisingly small and easy to use. It consists of a AA battery-operated, single-channel electrical stimulator, two electrodes, and electrode leads. WalkAide is applied directly to the leg — not implanted underneath the skin — which means no surgery is involved. A cuff holds the system comfortably in place, and it can be worn discreetly under most clothing. With the WalkAide’s patented Tilt Sensor technology, most users do not require additional external wiring or remote heel sensors.
WalkAide Provides the Advantages not Found in Typical Foot Drop Treamtents :
- Easy one-handed operation and application
- Small, self-contained unit
- Does not require orthopedic or special shoes
- May be worn barefoot or with slippers
- Minimal contact means minimal discomfort with reduced perspiration
- May improve circulation, reduce atrophy, improve voluntary control and increase joint range of motion
Customized For Individual Walking Pattern
WalkAide is not a one size fits all device. Rather, a specially trained medical professional customizes and fits the WalkAide. Using WalkAnalyst, a multifaceted computer software program, the clinician can tailor WalkAide to an individual’s walking pattern for optimal effectiveness.
Exercise Mode for Home Use
In addition fo walking assistance, the WalkAide system includes a pre-programmable exercise mode that allows a user to exercise his/her muscles while resting for a set period of time as prescribed.
OBJECTIVE. We quantified the range of motion (ROM) required for eight upper-extremity activities of daily living (ADLs) in healthy participants.
METHOD. Fifteen right-handed participants completed several bimanual and unilateral basic ADLs while joint kinematics were monitored using a motion capture system. Peak motions of the pelvis, trunk, shoulder, elbow, and wrist were quantified for each task.
RESULTS. To complete all activities tested, participants needed a minimum ROM of −65°/0°/105° for humeral plane angle (horizontal abduction–adduction), 0°–108° for humeral elevation, −55°/0°/79° for humeral rotation, 0°–121° for elbow flexion, −53°/0°/13° for forearm rotation, −40°/0°/38° for wrist flexion–extension, and −28°/0°/38° for wrist ulnar–radial deviation. Peak trunk ROM was 23° lean, 32° axial rotation, and 59° flexion–extension.
CONCLUSION. Full upper-limb kinematics were calculated for several ADLs. This methodology can be used in future studies as a basis for developing normative databases of upper-extremity motions and evaluating pathology in populations.