Posts Tagged Arm

[WEB PAGE] Upper arm rehabilitation after severe stroke: where are we? – Physics World

10 Sep 2019 Andrea Rampin 
EEG cap

Stroke is the second leading cause of death worldwide and the third cause of induced disability, according to estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study. Treatments based on constraint-induced movement therapy, occupational practice, virtual reality and brain stimulation can work well for patients with mild impairment of upper limb movement, but they are not as effective for those burdened by severe disability. Therefore, novel individualized approaches are needed for this patient group.

Martina Coscia from the Wyss Center for Bio and Neuroengineering in Geneva, and colleagues from several other Swiss institutes, have published a review paper summarizing the most advanced techniques in use today for treatment of severe, chronic stroke patients. The researchers describe techniques being developed for upper limb motor rehabilitation: from robotics and muscular electrical stimulation, to brain stimulation and brain–computer/machine interfaces (Brain 10.1093/brain/awz181).

Robot-aided rehabilitation approaches include movement-assisting exoskeletons and end-effector devices, which enable upper arm movement by stimulating the peripheral nervous system. These techniques can also trigger reorganization of the impaired peripheral nervous system and encourage rehabilitation of the damaged somatosensory system. Several studies have reported the efficiency of robot-aided rehabilitation, alone or in combination with other techniques, in the treatment of upper limb motor impairment. One study that included severely impaired individuals also demonstrated encouraging results.

Muscular electrical stimulation can help improve the connection of motor neurons to the spinal cord and the motor cortex. Researchers have also demonstrated that application of electrical stimuli to the muscles provides positive effects on the neurons responsible for sensory signal transduction to the brain, thereby improving the motion control loop function. By modulating motor neurons’ sensitivity, muscular electrical stimulation inhibits the muscle spasms observed in other treatments.

More recently, therapies have moved on from the simple use of currents to harnessing coordinated stimuli to orchestrate more complex, task-related movements. Although this particular set of techniques didn’t show a particular advantage over physiotherapy in long-term studies of patients with mild upper limb impairment, it did seem to have a stronger effect for chronic severe patients.

Stimulating the brain

Brain stimulation, meanwhile, stimulates cortical neurons in order to improve their ability to form new connections within the affected neural network. Brain stimulation techniques can be divided into two branches – electrical and magnetic – both of which can activate or inhibit neural activity, depending on the polarity and intensity of the stimulus.

Transcranial magnetic stimulation

Researchers have achieved encouraging results using both techniques. In particular, magnetic field-triggered inhibition of the contralesional hemisphere (the hemisphere that was not affected by the stroke) activity yielded positive results. Magnetic, low-frequency stimulation of the contralesional hemisphere also proved encouraging – improving the reach to grasp ability of patients, although only for small objects. Excitingly, some studies suggest that coupling contralesional cortex inhibition with magnetic stimulation of the chronically affected area could achieve effective results.

Within these techniques, one promising approach is invasive brain stimulation, in which a device is surgically implanted in a superficial region of the brain. Such techniques allow for more sustained and spatially-oriented stimulation of the desired brain regions. The Everest trial used such methods and showed significant improvement for a larger percentage of patients after 24 weeks, compared with standard rehabilitation protocols.

Another promising recent development is non-invasive deep-brain stimulation, achieved by temporally interfering electric fields. The authors envision that a deeper understanding of the complex mechanisms involved in the brain’s reactions to magnetic and electrical stimulation will provide an important assistance in clinical application of these techniques.

The final category, brain–computer or brain–machine interfaces (BCIs or BMIs), exploit electroencephalogram (EEG) patterns to trigger feedback or an action output from an external device. Devices that produce feedback are used to train the patient to recruit the correct zone of the brain and help reorganize its interconnections. These techniques have only recently transitioned to the clinic; however, early results and observations are promising. For example, a BCI technique coupled with muscular electrical stimulation restored patients’ ability to extend their fingers.

In recent years, researchers have also tested combinations of the techniques described above. For example, combinations of robotics and muscular electrical stimulation have shown encouraging results, especially when more than one articulation was targeted by the treatment. Combining brain stimulation with muscular electrical stimulation and robotics has proved more effective in severe than in moderate cases. Also, coupling of muscular electrical stimulation with magnetic inhibitory brain stimulation provided better results than either individual technique. Interestingly, addition of electrical brain stimulation to a BCI system coupled with a robotic motor feedback enhanced the outcome, helping to achieve adaptive brain remodelling at the expense of inappropriate reorganization.

Coscia and co-authors highlight that all the techniques studied share a range of limitations that should be addressed, such as small sample size, limited understanding of the underlying mechanisms, lack of treatment personalization and minimal attention to the training task, which they note is often of limited importance for daily life. Addressing these limitations might be key to improving the clinical outcome for patients with severe stroke-induced upper limb paralysis treated with neurotechnology-aided interventions. Moreover, the authors plan to begin a clinical trial to test the use of a novel personalized therapy approach that will include a combination of the described techniques.

 

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[VIDEO] Stroke Rehabilitation: Use of electrical stimulation to help arm and hand recovery

This video demonstrates how to use FES, Functional Electrical Stimulation, to engage the muscles of the arm to extend the fingers.

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[ARTICLE] Evaluation of a 1-DOF Hand Exoskeleton for Neuromuscular Rehabilitation – Full Text PDF

Abstract

A low-cost 1-DOF hand exoskeleton for neuromuscular rehabilitation has been designed and assembled. It consists of a base equipped with a servo motor, an index finger part, and a thumb part, connected through three gears. The index part has a tri-axial load cell and an attached ring to measure the finger force. An admittance control scheme was designed to provide intuitive control and positive force amplification to assist the user’s finger movement. To evaluate the effects of different control parameters on neuromuscular response of the fingers, we created an integrated exoskeleton-hand musculoskeletal model to virtually simulate and optimize the control loop. The exoskeleton is controlled by a proportional derivative controller that computes the motor torque to follow a desired joint angle of the index part, which is obtained from inverse kinematics of a virtual end-effector mass driven by the finger force. We conducted parametric simulations of the exoskeleton in action, driven by the user’s
closing and opening finger motion, with different proportional gains, endeffector masses, and other coefficients. We compared the interaction forces between the index finger and the ring in both passive and active modes. The best performing assistive controller can reduce the force from around 1.45N (in passive mode) to only around 0.52N, more than 64% of reduction. As a result, the muscle activations of the flexors and extensors were reduced significantly. We also noted the admittance control scheme is versatile and can also provide resistance (e.g. for strength training) by simply increasing the virtual end-effect mass.

1 Introduction

Stroke, one of the leading causes of adult disability, affects approximately 800,000 individuals each year in the United States [1]. Nearly 80% of stroke survivors suffer
from hemiparesis of the upper arm and thus impaired hand function, which is integral
to most activities of daily living. It is well established that highly repetitive training
can aid in the recovery of motor function of the hand however this can be labor intensive for the providing physical therapist in addition to the cost. In the past decade,
more robotic hand rehabilitation devices have been introduced to help patients recover
hand function through assistance during repetitive training of the hand [2-4].
In a comprehensive review by Heo et al. [2], hand exoskeleton technologies for rehabilitation and assistive engineering, from basic hand biomechanics, neurophysiology, sensors and actuators, physical human-robot interactions and ergonomics, are summarized. Different types of actuators and control schemes have been used for hand exoskeletons. In some control schemes, the robotic device will move the user passively through a preprogrammed trajectory for continuous passive movement (CPM) therapy. These devices can be beneficial for severely impaired individuals who may not have the ability to generate the forces required for specific finger or hand movement or for individuals who have abnormal muscle synergies preventing continuous movement. A few devices such as the Kinetic Maestra and Vector 1 are commercially available devices that are used for CPM [5, 6]. These devices allow for
passive movement through the range of motion for individual fingers. However, as
there is no active participation by the user, this device on its own may not promote
neurorehabilitation. These devices can be combined with other simulations or control
schemes that require active participation by the user. One commercially available
hand exoskeleton that has been used extensively by our lab to provide haptics to virtual simulations is the CyberGrasp [7]. The CyberGrasp is a cable driven exoskeleton
that weighs 450 grams and can provide up to 12 N of force on each finger and can be
used to provide assistance for extension of the user’s fingers. In one study, this was
used in combination with a virtual reality simulation to train finger individuation as
the user played a virtual piano [8]. The CyberGrasp was used to resist finger flexion
of the inactive fingers, promoting movement of the active independent finger. Similarly, the eXtension Glove (X-Glove) was developed to be used for cyclical stretching
in addition to active movement training [9-11]. This cable driven design is actuated
using linear servos allowing for individual finger movement in both extension and
flexion. In addition to this, each cable is integrated with a tension sensor which allows
the force of each digit to be monitored. This device has two modes that can be used
for rehabilitation, the first mode cyclically extends and flexes the fingers. The second
mode is an active training mode in which the glove provides constant extension assistance so that the user can complete flexion tasks as long as they overcome the force
required to keep the finger extended. In a further attempt to integrate user control with
the exoskeleton, an external input from the user such as force or electromyography
has been incorporated into some designs such as the Helping Hand [12]. This soft
robotic device allows for active assistance for each finger individually, in addition to
the ability to follow control states triggered by EMG.

In this paper, we introduce a low cost 1-DOF hand exoskeleton for neuromuscular
rehabilitation of individual fingers. This exoskeleton consists of a base equipped with
a servo motor, an index finger component and a thumb component connected with
gears. The exoskeleton’s control system was designed to generate suitable actuation
torques based on the interaction force between the user’s finger and the exoskeleton’s
index component. The goal of this study is to model the exoskeleton interacting with a
neuromuscular hand model in order to evaluate the effectiveness of an intuitive admittance control algorithm on providing different levels of assistance or resistance during hand rehabilitation.

2 Methods

2.1 The 1-DOF Exoskeleton and Hand Model

This exoskeleton consists of a base stationed with a servo motor (Dynamixel
XM430), an index finger part and a thumb part, which are connected through 3 gears
of equal sizes as shown in Fig. 1. The motor drives the top gear which in turn rotates
the gear attached to the index part and then the gear attached the thumb part. The
index and thumb parts both have rings for the fingers, and an OptoForce tri-axial load
cell or force sensor (OnRobot, Denmark) is attached to the index ring. All parts are
3D printed with a carbon fiber reinforced nylon material called Onyx (Markforged,
USA). The total weight of this exoskeleton is 0.158kg and the mass and inertia properties of its components, which were either measured or computed based on material
and part geometry, are listed in Table 1.

Related image

Fig. 1. The design of the 1-DOF hand exoskeleton

Full Text PDF

 

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[Abstract + References] Preliminary Design of Soft Exo-Suit for Arm Rehabilitation – Conference paper

Abstract

Every year, millions of people experience a stroke but only a few of them fully recover. Recovery requires a working staff, which is time consuming and inefficient. Therefore, over the past few years rehabilitation robots like Exoskeletons have been used in the recuperation process for patients. In this paper we have designed an Exosuit which takes into considerations of the rigid Exo-Skeleton and its limitations for patients suffering from loss of function of the arm. This paper concentrates on enabling a stroke affected person to perform flexion-extension at elbow joint. Validation of the developed model on general population is still needed.

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[Abstract + References] Arm Games for Virtual Reality Based Post-stroke Rehabilitation – Conference paper

Abstract

Stroke is a leading cause of serious long-term disability. World Health Organization (WHO) published that the second leading of death is stroke accident and every year, 15 million people worldwide suffer from stroke attack, two-thirds of them have a permanent disability. Muscle impairment can be treated by intensive movements involving repetitive task, task-oriented and task-variegated. Conventional stroke rehabilitation is expensive, less engaging and at the same time need more time for the rehabilitation process and need more energy and time for the therapist to guide the stroke-survivor. Modern stroke rehabilitation is more promising and more effective with modern rehabilitation aids allowing the rehabilitation process to be faster, however, this therapist method can be obtained in the big cities. To cover the lack of rehabilitation process in this research will develop and improve post-stroke rehabilitation using games. This research using electromyography (EMG) device to analyze the muscle contraction during the rehabilitation process and using Kinect XBOX to record trajectory hands movements. Five games from movements sequence have designed and will be examined in this research. This games obtained two results, the first is the EMG signal and the second is trajectory data. EMG signal can recognize muscle contractions during playing game and the trajectory data can save the pattern of movements and showed the pattern to the monitor. EMG signal processing using time or frequency feature extractions is a good idea to obtain more information from muscle contractions, also velocity, similarities and error movements can be obtained by study the possible approaches.

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[WEB SITE] Telerehab Program Works as Well as Clinic-Based Program for Improved Arm Function Poststroke – JAMA Neurology

It’s probably not news to physical therapists (PTs) when research backs up the idea that patients who experience arm impairments poststroke will tend to make greater functional improvements with larger and longer doses of rehabilitation. Unfortunately, PTs are also familiar with the fact that what’s optimal isn’t necessarily what’s typical, with challenges such as payment systems, logistics, and clinic access making it difficult to achieve the best possible results. That’s where telerehabilitation could make a big difference, say authors of a new study that found an entirely remotely delivered rehab program to be as effective as an equal amount of clinic-based sessions.

The findings lend further support to the ideas behind APTA’s efforts to increase telehealth opportunities for PTs and their patients—a significant component of the association’s current public policy priorities. In addition, APTA provides multiple telehealth resources on a webpage devoted to the topic, and has created the Frontiers in Research, Science, and Technology Council that provides interested members and other stakeholders with an online community to discuss technology’s role in physical therapy.

The study, published in JAMA Neurology (abstract only available for free), involved 124 participants who experienced arm motor deficits poststroke. All participants were enrolled in a rehabilitation therapy program that included 36 70-minute treatment sessions, half of which were supervised, over a 6- to 8-week period. The only major difference: one group’s supervised sessions were face-to-face with a physical therapist (PT) or occupational therapist (OT), while the other group received telerehab from a PT or OT via a computer with video capabilities, accompanied by the use of a gaming system.

Researchers were interested in finding out how patients fared in each approach, using scores from the Fugl Meyer (FM) assessment of motor recovery poststroke as their primary measure. Authors of the study also measured patient adherence with therapy as well as levels of patient motivation related to how well they liked the therapy they were receiving and their degree of dedication to treatment goals.

Using a treatment approach “based on an upper-extremity task-specific training manual and Accelerated Skill Acquisition Program,” researchers set up matched programs that included at least 15 minutes per session of arm exercises from a common set of 88 possible exercises, at least 15 minutes of functional training, and 5 minutes of stroke education. The clinic-based participants received in-person instruction on the exercises and used “standard exercise hardware”; the telerehab patients received instructions via video link and engaged in functional exercise via a videogame interface. Here’s what the researchers found:

  • Both groups improved at about the same rate, with the telerehab participants averaging a 7.86 FM gain, compared with an average gain of 8.36 points for the clinic-based group.
  • Improvements were also about the same for the subgroup of participants who entered rehabilitation more than 90 days poststroke, with these “late” participants averaging a 6.6-point gain for the telerehab group and a 7.4-point increase for the clinic-based group.
  • While both groups reported high levels of dedication to treatment goals, the clinic-based group tended to report better levels of motivation and satisfaction. Adherence was also high for both groups, with a 93.4% adherence rate for the clinic-based group and a rate of 98.3% for the telerehab group.
  • Both groups increased their knowledge of stroke at similar rates.

As for the technical details of the telerehab sessions, the system included a computer linked to the internet, a table, a chair, and 12 “gaming input devices.” Keyboards were not necessary. The supervised sessions began with a 30-minute videoconference between the patient and therapist, and the functional training games used were designed to match the functional task work being done with the clinic-based participants. Unsupervised sessions adhered to the same content but didn’t include contact with the therapist.

“In an era when prescribed doses of poststroke rehabilitation therapy are declining, adversely affecting patient outcomes, these and prior findings suggest that outcomes could be improved for many patients…if larger doses of rehabilitation therapy were prescribed,” authors write. “Our study found that a 6-week course of daily home-based [telerehab] is safe, is rated favorably by patients, is associated with excellent treatment adherence, and produces substantial gains in arm function that were not inferior to dose-matched interventions delivered in the clinic.”

Authors acknowledged that patient satisfaction with telerehab might be improved by increasing the amount of time spent with the therapist—providing that therapist is properly trained. “Current results underscore the importance of maintaining a licensed therapist’s involvement during [telerehab],” they write.

Ultimately, it’s still too early to determine just how generalizable the findings are to other populations and conditions, the researchers say, but all indicators seem to point to the need for increasing the availability of telerehab and its inclusion in health plans.

“The US Bipartisan Budget Act of 2018 expanded telehealth benefits,” authors write. “Eventually, home-based [telerehab] may plan an ascendant role for improving patient outcomes.”

Research-related stories featured in PT in Motion News are intended to highlight a topic of interest only and do not constitute an endorsement by APTA. For synthesized research and evidence-based practice information, visit the association’s PTNow website.

via JAMA Neurology: Telerehab Program Works as Well as Clinic-Based Program for Improved Arm Function Poststroke

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[ARTICLE] Neurotechnology-aided interventions for upper limb motor rehabilitation in severe chronic stroke – Full Text

Abstract

Upper limb motor deficits in severe stroke survivors often remain unresolved over extended time periods. Novel neurotechnologies have the potential to significantly support upper limb motor restoration in severely impaired stroke individuals. Here, we review recent controlled clinical studies and reviews focusing on the mechanisms of action and effectiveness of single and combined technology-aided interventions for upper limb motor rehabilitation after stroke, including robotics, muscular electrical stimulation, brain stimulation and brain computer/machine interfaces. We aim at identifying possible guidance for the optimal use of these new technologies to enhance upper limb motor recovery especially in severe chronic stroke patients. We found that the current literature does not provide enough evidence to support strict guidelines, because of the variability of the procedures for each intervention and of the heterogeneity of the stroke population. The present results confirm that neurotechnology-aided upper limb rehabilitation is promising for severe chronic stroke patients, but the combination of interventions often lacks understanding of single intervention mechanisms of action, which may not reflect the summation of single intervention’s effectiveness. Stroke rehabilitation is a long and complex process, and one single intervention administrated in a short time interval cannot have a large impact for motor recovery, especially in severely impaired patients. To design personalized interventions combining or proposing different interventions in sequence, it is necessary to have an excellent understanding of the mechanisms determining the effectiveness of a single treatment in this heterogeneous population of stroke patients. We encourage the identification of objective biomarkers for stroke recovery for patients’ stratification and to tailor treatments. Furthermore, the advantage of longitudinal personalized trial designs compared to classical double-blind placebo-controlled clinical trials as the basis for precise personalized stroke rehabilitation medicine is discussed. Finally, we also promote the necessary conceptual change from ‘one-suits-all’ treatments within in-patient clinical rehabilitation set-ups towards personalized home-based treatment strategies, by adopting novel technologies merging rehabilitation and motor assistance, including implantable ones.

Introduction

Stroke constitutes a major public health problem affecting millions of people worldwide with considerable impacts on socio-economics and health-related costs. It is the second cause of death (Langhorne et al., 2011), and the third cause of disability-adjusted life-years worldwide (Feigin et al., 2014): ∼8.2 million people were affected by stroke in Europe in 2010, with a total cost of ∼€64 billion per year (Olesen et al., 2012). Due to ageing societies, these numbers might still rise, estimated to increase 1.5–2-fold from 2010 to 2030 (Feigin et al., 2014).

Improving upper limb functioning is a major therapeutic target in stroke rehabilitation (Pollock et al., 2014Veerbeek et al., 2017) to maximize patients’ functional recovery and reduce long-term disability (Nichols-Larsen et al., 2005Veerbeek et al., 2011Pollock et al., 2014). Motor impairment of the upper limb occurs in 73–88% first time stroke survivors and in 55–75% of chronic stroke patients (Lawrence et al., 2001). Constraint-induced movement therapy (CIMT), but also standard occupational practice, virtual reality and brain stimulation-based interventions for sensory and motor impairments show positive rehabilitative effects in mildly and moderately impaired stroke victims (Pollock et al., 2014Raffin and Hummel, 2018). However, stroke survivors with severe motor deficits are often excluded from these therapeutic approaches as their deficit does not allow easily rehabilitative motor training (e.g. CIMT), treatment effects are negligible and recovery unpredictable (Byblow et al., 2015Wuwei et al., 2015Buch et al., 2016Guggisberg et al., 2017).

Recent neurotechnology-supported interventions offer the opportunity to deliver high-intensity motor training to stroke victims with severe motor impairments (Sivan et al., 2011). Robotics, muscular electrical stimulation, brain stimulation, brain computer/machine interfaces (BCI/BMI) can support upper limb motor restoration including hand and arm movements and induce neuro-plastic changes within the motor network (Mrachacz-Kersting et al., 2016Biasiucci et al., 2018).

The main hurdle for an improvement of the status quo of stroke rehabilitation is the fragmentary knowledge about the physiological, psychological and social mechanisms, their interplay and how they impact on functional brain reorganization and stroke recovery. Positive stimulating and negatively blocking adaptive brain reorganization factors are insufficiently characterized except from some more or less trivial determinants, such as number and time of treatment sessions, pointing towards the more the better (Kwakkel et al., 1997). Even the long accepted model of detrimental interhemispheric inhibition of the overactive contralesional brain hemisphere on the ipsilesional hemisphere is based on an oversimplification and lack of differential knowledge and is thus called into question (Hummel et al., 2008Krakauer and Carmichael, 2017Morishita and Hummel, 2017).

Here, we take a pragmatic approach of comparing effectiveness data, keeping this lack of knowledge of mechanisms in mind and providing novel ideas towards precision medicine-based approaches to individually tailor treatments to the characteristics and needs of the individual patient with severe chronic stroke to maximize rehabilitative outcome.[…]

Continue —>   Neurotechnology-aided interventions for upper limb motor rehabilitation in severe chronic stroke | Brain | Oxford Academic

Conceptualization of longitudinal personalized rehabilitation-treatment designs for patients with severe chronic stroke. Ideally, each patient with severe chronic stroke with a stable motor recovery could be stratified based on objective biomarkers of stroke recovery in order to select the most appropriate/promising neurotechnology-aided interventions and/or their combination for the specific case. Then, these interventions can be administered in the clinic and/or at home in sequence, moving from one to another only when patient’s motor recovery plateaus. In this way, comparisons of the efficacy of each intervention (grey arrows) are still possible, and if the selected interventions and/or their combination are suitable, motor recovery could increase.

Conceptualization of longitudinal personalized rehabilitation-treatment designs for patients with severe chronic stroke. Ideally, each patient with severe chronic stroke with a stable motor recovery could be stratified based on objective biomarkers of stroke recovery in order to select the most appropriate/promising neurotechnology-aided interventions and/or their combination for the specific case. Then, these interventions can be administered in the clinic and/or at home in sequence, moving from one to another only when patient’s motor recovery plateaus. In this way, comparisons of the efficacy of each intervention (grey arrows) are still possible, and if the selected interventions and/or their combination are suitable, motor recovery could increase.

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[NEWS] NEOFECT Wins Design Week VirtualTech Award for Second Year In a Row

Published on 

SmartBoardforHome

NEOFECT was once again honored at the San Francisco Design Week (SFDW) Awards, winning the VirtualTech award for its new Smart Board for Home NextGen, a gamified rehabilitation device for stroke survivors to use at home.

This marks the second consecutive year that the company has received the VirtualTech award, according to a company announcement.

“The Smart Board for Home NextGen is the epitome of the 2019 SFDW Awards theme, and we’re humbled to have won this year after receiving Honorable Mention in the VirtualTech category last year for our Smart Glove for Home,” says Scott Kim, co-founder and CEO of NEOFECT USA, in the release.

“We took every aspect of the patient experience into account when redesigning the Smart Board for Home NextGen,” Kim adds.

“For example, stroke patients’ grip is often weak, so we re-engineered the handle to be more secure. We developed more interactive virtual reality games, like tennis, so patients can have more variety, and also created a dual-player option.”

SFDW is an international design competition that honors projects encouraging thought leadership in design, focusing on “Where Innovation Meets Social Responsibility.”

The awards celebrate and recognize exemplary work in all fields of design, including architecture, interior design, industrial design, communication design, and user experience design.

Twenty-four winning projects and 11 honorable mentions were selected by a jury comprised of professionals—including executives from Lyft, Google, Microsoft, and Fitbit—who reviewed submissions from a pool of applicants from the USA and Europe. Each winning project was judged based on impact, singularity, inclusiveness, social responsibility, ease of use, visual appeal, and feasibility.

Award winners from leading design firms, in-house teams, and creative individuals were honored recently during a ceremony that took place at Pier 27 in San Francisco, the release explains.

“We are extremely excited the San Francisco Design Week Awards returned this year,” states SFDW Executive Director Dawn Zidonis.

“As with last year, the quality of the many entries exceeded our expectations. Congratulations to this year’s outstanding and diverse winners, including NEOFECT.”

[Source(s): NEOFECT, Business Wire]

 

via NEOFECT Wins Design Week VirtualTech Award for Second Year In a Row – Rehab Managment

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[Abstract] Differential Poststroke Motor Recovery in an Arm Versus Hand Muscle in the Absence of Motor Evoked Potentials

Background. After stroke, recovery of movement in proximal and distal upper extremity (UE) muscles appears to follow different time courses, suggesting differences in their neural substrates.

Objective. We sought to determine if presence or absence of motor evoked potentials (MEPs) differentially influences recovery of volitional contraction and strength in an arm muscle versus an intrinsic hand muscle. We also related MEP status to recovery of proximal and distal interjoint coordination and movement fractionation, as measured by the Fugl-Meyer Assessment (FMA).

Methods. In 45 subjects in the year following ischemic stroke, we tracked the relationship between corticospinal tract (CST) integrity and behavioral recovery in the biceps (BIC) and first dorsal interosseous (FDI) muscle. We used transcranial magnetic stimulation to probe CST integrity, indicated by MEPs, in BIC and FDI. We used electromyography, dynamometry, and UE FMA subscores to assess muscle-specific contraction, strength, and inter-joint coordination, respectively.

Results. Presence of MEPs resulted in higher likelihood of muscle contraction, greater strength, and higher FMA scores. Without MEPs, BICs could more often volitionally contract, were less weak, and had steeper strength recovery curves than FDIs; in contrast, FMA recovery curves plateaued below normal levels for both the arm and hand.

Conclusions. There are shared and separate substrates for paretic UE recovery. CST integrity is necessary for interjoint coordination in both segments and for overall recovery. In its absence, alternative pathways may assist recovery of volitional contraction and strength, particularly in BIC. These findings suggest that more targeted approaches might be needed to optimize UE recovery.

 

via Differential Poststroke Motor Recovery in an Arm Versus Hand Muscle in the Absence of Motor Evoked Potentials – Heidi M. Schambra, Jing Xu, Meret Branscheidt, Martin Lindquist, Jasim Uddin, Levke Steiner, Benjamin Hertler, Nathan Kim, Jessica Berard, Michelle D. Harran, Juan C. Cortes, Tomoko Kitago, Andreas Luft, John W. Krakauer, Pablo A. Celnik, 2019

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[NEWS] NEOFECT Redesigns Smart Board for Home

Published on May 8, 2019

SmartBoardforHome

NEOFECT has redesigned its Smart Board for Home in reply to feedback from patients recovering from stroke and other musculoskeletal conditions and neurological disorders.

The new Smart Board for Home NextGen includes a smaller surface to help patients use it at home more easily, a redesigned handle to better stabilize the user’s hand and arm, and updated gamified software.

The board size has been reduced from 42 inches to 32 inches so it can fit on most tables. To accommodate the weakened grip of many stroke patients, the redesigned handle includes more straps to better stabilize the user’s arm, ensure appropriate measurement for the post-game metrics, and provide a more secure, comfortable experience, according to the company in a media release.

“We took patient feedback and completely revamped the Smart Board for Home NextGen,” says Scott Kim, co-founder and CEO of San Francisco-based NEOFECT USA.

“This new model still has all the fun, measurable qualities patients can use at home, but now we’ve reduced even more barriers so that people of all abilities can gain back function in their hands and upper arms.”

Patients play games on the Smart Board for Home NextGen by placing their forearm in a cradle and moving their arm across the board. All movements are virtually mimicked on a Bluetooth-connected screen in real time. The gamified software also features an updated AI-powered algorithm to curate a more customized experience for each patient.

The Smart Board for Home NextGen games mimic real-world motions to rehabilitate users’ upper arms and shoulders, including new games like “Air Hawk” and “Tennis.”

Additionally, NEOFECT is developing a dual-player game for patients to use at home, which will be available in summer 2019.

[Source(s): NEOFECT, Business Wire]

Source:
http://www.rehabpub.com/2019/05/neofect-redesigns-smart-board-home/

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