Showing posts with label 30% get spasticity. Show all posts
Showing posts with label 30% get spasticity. Show all posts
Monday, February 10, 2025
Saturday, February 1, 2025
Harvard Move Lab makes wearable robotic devices for stroke victims
But does it work for the 30% of survivors that have spasticity? Without curing spasticity, smooth movement is a bitch.
Harvard Move Lab makes wearable robotic devices for stroke victims
Harvard University's Move Lab has developed a wearable robotic device aimed at helping stroke survivors and people with movement impairments regain mobility.
Dubbed Reachable, this device can provide at-home therapy and enable independence in everyday tasks such as cleaning, while delivering therapeutic benefits.
Design and Functionality
The product is lightweight and can be worn like a harness. It contains a soft under-arm balloon that inflates and deflates, fitted with sensors that track the user's movement.
These sensors understand the user's progress and adapt the level of support accordingly.
Therapeutic Effects
The technology is designed to immediately start exercising muscles to help the brain relearn.
Funding and Development
The Reachable team recently received a three-year, $5 million grant from the U.S. National Science Foundation to expedite the transition of practical research into the marketplace.
The team received Phase 2 funding in 2023, with the Move Lab as a core partner, to continue testing and refining the device, aiming for eventual licensing to a company.
Collaborations and Research
The Move Lab is also funded by the National Institutes of Health to develop a neuroprosthesis for improving mobility for stroke survivors. In a past project, Move Lab researchers developed new technology for measuring sensation and muscle activity.
Reachable's partners include Massachusetts General Hospital, Cecropia Strong, Imago Rehab, Simbex Product Development, and others.
Expert Insights
“After a stroke, the wearable robotic device’s control system that synchronises and initiates all the movements that’s broken – not the muscles,” said Executive Director Paul Sabin in the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS).“If we can get this to people before their muscles atrophy or before the disease progresses, then they can focus on trying to recover their control system.”
Saturday, December 28, 2024
Direction-specific Disruption of Paretic Arm Movement in Post-stroke Patients
To get any arm reaching movements at all, I'd need my spasticity cured. So from that perspective this was totally useless research for the 30% of survivors that have spasticity!
Direction-specific Disruption of Paretic Arm Movement in Post-stroke Patients
Kiyoshi Yoshioka, RPT, PhD
a,*
Tatsunori Watanabe, RPT, PhD
b,*
Mizuki Yoshioka, RPT
a
Keita Iino, RPT
a
Kimikazu Honda, RPT
a
Koshiro Hayashida, RPT
a
and Yuji Kuninaka, RPT
Objective:
This study aimed to characterize reaching movements of the paretic arm in diferent
directions within the reachable workspace in post-stroke patients.
Methods:
A total of 12 post-
stroke patients participated in this study. Each held a ball with a tracking marker and performed
back-and-forth reaching movements from near the middle of the body to one of two targets in front
of them located on the ipsilateral and contralateral sides of the arm performing the movement. We
recorded and analyzed the trajectories of the tracking marker. The stability of arm movements
was evaluated using areas and minimum Feret diameters to assess the trajectories of both the
paretic and non-paretic arms. The speed of the arm movement was also calculated.
Results:
For
the paretic arm, contralateral movement was more impaired than ipsilateral movement, whereas
for the non-paretic arm, no diference was observed between the directions. The maximum speed
of the contralateral movement was signifcantly slower than that of the ipsilateral movement in
both the paretic and non-paretic arms.
Conclusion:
The paretic arm shows direction-specifc
instability in movement toward the contralateral side of the arm.
Tuesday, January 16, 2024
‘Smart glove’ can boost hand mobility of stroke patients
For the third of stroke patients that have spasticity this would be impossible to put on! Do people in stroke ever THINK AT ALL?
30% get spasticity (24 posts to March 2016)
‘Smart glove’ can boost hand mobility of stroke patients
This month, a group of stroke survivors in B.C. will test a new technology designed to aid their recovery, and ultimately restore use of their limbs and hands.
Participants will wear a groundbreaking “smart glove” capable of tracking their hand and finger movements(Meaning you are using this for high functioning patients already! The goal in stroke is to 'Leave no survivors behind!) during rehabilitation exercises supervised by Dr. Janice Eng, a leading stroke rehabilitation specialist and professor of physical therapy at UBC’s faculty of medicine.
The glove incorporates a sophisticated network of highly sensitive sensor yarns and pressure sensors that are woven into a comfortable stretchy fabric, enabling it to track, capture and wirelessly transmit even the smallest hand and finger movements.
“With this glove, we can monitor patients’ hand and finger movements without the need for cameras. We can then analyze and fine-tune their exercise programs for the best possible results, even remotely,” says Dr. Eng.
Precision in real time
The smart glove was created for the stroke project by UBC professor Dr. Peyman Servati and PhD student Arvin Tashakori, from the department of electrical and computer engineering, and the team at their startup, Texavie. Dr. Servati highlighted a number of breakthroughs.
“This is the most accurate glove we know of that can track hand and finger movement and grasping force without requiring motion-capture cameras. Thanks to machine learning models we developed, the glove can accurately determine the angles of all finger joints and the wrist as they move. The technology is highly precise and fast, capable of detecting small stretches and pressures and predicting movement with at least 99-per-cent accuracy – matching the performance of costly motion-capture cameras.”
Unlike other products, the glove is wireless and comfortable, and can be easily washed after removing the battery. Dr. Servati and his team have developed advanced methods to manufacture the smart gloves and related apparel at a relatively low cost locally.
Augmented reality and robotics
Dr. Servati envisions a seamless transition of the glove into the consumer market with ongoing improvements, in collaboration with different industrial partners. The team also sees potential applications in virtual reality and augmented reality, animation and robotics.
“Imagine being able to accurately capture hand movements and interactions with objects and have it automatically display on a screen. There are endless applications. You can type text without needing a physical keyboard, control a robot, or translate American Sign Language into written speech in real time, providing easier communication for individuals who are deaf or hard of hearing.”
The research findings were published in Nature Machine Intelligence.
Saturday, July 1, 2023
Ankle-targeted exosuit resistance increases paretic propulsion in people post-stroke
I see nothing here that suggests they are solving the spasticity problem in walking.
Since 30% of survivors that have spasticity, they are screwed in walking recovery.
Right now I have zero propulsion, the whole leg is swung from the hip.
Ankle-targeted exosuit resistance increases paretic propulsion in people post-stroke
Journal of NeuroEngineering and Rehabilitation volume 20, Article number: 85 (2023)
Abstract
Background
Individualized, targeted, and intense training is the hallmark of successful gait rehabilitation in people post-stroke. Specifically, increasing use of the impaired ankle to increase propulsion during the stance phase of gait has been linked to higher walking speeds and symmetry. Conventional progressive resistance training is one method used for individualized and intense rehabilitation, but often fails to target paretic ankle plantarflexion during walking. Wearable assistive robots have successfully assisted ankle-specific mechanisms to increase paretic propulsion in people post-stroke, suggesting their potential to provide targeted resistance to increase propulsion, but this application remains underexamined in this population. This work investigates the effects of targeted stance-phase plantarflexion resistance training with a soft ankle exosuit on propulsion mechanics in people post-stroke.
Methods
We conducted this study in nine individuals with chronic stroke and tested the effects of three resistive force magnitudes on peak paretic propulsion, ankle torque, and ankle power while participants walked on a treadmill at their comfortable walking speeds. For each force magnitude, participants walked for 1 min while the exosuit was inactive, 2 min with active resistance, and 1 min with the exosuit inactive, in sequence. We evaluated changes in gait biomechanics during the active resistance and post-resistance sections relative to the initial inactive section.
Results
Walking with active resistance increased paretic propulsion by more than the minimal detectable change of 0.8 %body weight at all tested force magnitudes, with an average increase of 1.29 ± 0.37 %body weight at the highest force magnitude. This improvement corresponded to changes of 0.13 ± 0.03 N m kg− 1 in peak biological ankle torque and 0.26 ± 0.04 W kg− 1 in peak biological ankle power. Upon removal of resistance, propulsion changes persisted for 30 seconds with an improvement of 1.49 ± 0.58 %body weight after the highest resistance level and without compensatory involvement of the unresisted joints or limb.
Conclusions
Targeted exosuit-applied functional resistance of paretic ankle plantarflexors can elicit the latent propulsion reserve in people post-stroke. After-effects observed in propulsion highlight the potential for learning and restoration of propulsion mechanics. Thus, this exosuit-based resistive approach may offer new opportunities for individualized and progressive gait rehabilitation.
Background
Stroke is a leading cause of motor disability, with over 100 million survivors worldwide [1]. Of these survivors, over 80% are left with locomotor dysfunction [2], resulting in slow and asymmetric gait presentations [3]. The incidence of stroke is projected to continue increasing over the next few decades [4], and thus presents an imminent challenge for independence and quality of life [5] for members of our communities. Reduced propulsive force generated by the paretic, or more affected, limb is a major contributor to these impairments, and leads to the inability of the individual to effectively propel the body forward [6]. This reduced paretic propulsion is partially due to weakness in the paretic ankle plantarflexor muscles [7], which leads to reduced ankle torque production, a key driver of propulsion [8]. Consequently, there is growing interest in rehabilitation programs that aim to increase paretic propulsion by targeting ankle function during the stance phase, when forward propulsion is generated, towards achieving the functional outcome of increased gait speed [9].
Among methods that improve speed and propulsion, those that elicit the latent propulsion reserve through high-intensity training have been shown to be particularly promising [10]. The presence of latent propulsion reserve is typically demonstrated as an increase in an individual’s propulsion while increasing the difficulty of the locomotor task, such as by increasing surface inclination [11] or resisting the entire body during walking [12]. However, this extra propulsion can be generated by ankle-level mechanisms (i.e., ankle kinetics) or limb-level mechanisms (i.e., proximal kinematics) [8]. Simulations suggest that traditional methods of engaging the latent propulsion reserve, such as through passive resistive elements acting on the patient’s limbs (e.g., elastic bands attached at the pelvis opposing forward motion, or weights added to the foot) [12,13,14], typically result in larger involvement of the proximal joints and affect the entire gait cycle rather than targeting the ankle in stance [15]. Over the past two decades, several wearable robotic systems for assisting the ankle during walking have demonstrated the ability to increase paretic propulsion [16] through ankle-specific mechanisms [17]. Based on the principles of high-intensity and task-specific training [18], a wearable robotic system that resists the ankle during walking may be an important approach, particularly for patients with higher propulsive capacities. Currently, however, targeted resistance training of the paretic ankle plantarflexors during stance for people post-stroke has yet to be investigated.
Most robotic systems developed for resistance training emulate conventional methods [19,20,21,22], resulting in a lack of specificity to paretic propulsion. Wearable devices offer the capability to provide controlled torques to target a specific joint and phase in the gait cycle. Consequently, some groups have developed systems for targeted swing-phase resistance in post-stroke [23] and healthy populations [24, 25], and have shown adaptations in joint kinematics that indicate increased ankle use. More recent work has shown that targeted stance-phase resistance can increase plantarflexor muscle activity in people with cerebral palsy [26] and healthy individuals [27, 28]. However, people post-stroke present with gait biomechanics and adaptation responses to perturbations that are different from both of these populations [29,30,31,32]. Thus, there is a need to explore the use of a wearable resistive robotic system for increasing paretic propulsion in stance for people post-stroke.
One challenge for developing a resistive paradigm with a wearable device is identifying the appropriate parameters of resistance. Prior literature has shown the sensitivity of users to the magnitude of active ankle resistance in able-bodied individuals [28] and passive resistance in post-stroke individuals [33]. For example, excessive resistance can lead to compensatory gait patterns that increase use of the unresisted proximal joints or limb, as evidenced by changes in limb loading or joint kinematics. Perspectives from the challenge point theory [34, 35] further support the importance of individualizing the challenge level during training to maximize retention of the learned task. Thus, there is a need for structured investigation of the effects of resistance parameters on post-stroke gait response to stance-phase ankle resistance.
An effective resistance training paradigm is one that induces learning of increased ankle use towards generating propulsion. Evidence of learning in the motor learning field is often obtained from after-effects in the few steps immediately following a perturbation [25, 27, 36], representing the persistence of an individual’s adapted state [37]. However, measuring after-effects following exoskeleton-based training has traditionally been challenging due to the added distal inertia of rigid devices, which requires a user to first doff the device, and thus may prevent capturing newly learned gait patterns. By design, the cable-driven soft exosuit only consists of textile components at the distal end of the leg, and hence can be rapidly commanded to apply no forces by releasing tension in the cables (< 50ms) [38]. In this “slack” mode, the device is transparent to the user, resulting in similar kinematics and energetics to when walking without any device [39, 40]. This transparency allows for the measurement of gait immediately after resistance without stopping walking. This approach has been used to measure changes in ankle kinematics in healthy individuals after ankle-targeted resistance [28], but has yet to be applied to people post-stroke.
In this work, we leverage a soft, cable-driven, unilateral ankle exosuit [41] to investigate the biomechanical effects of targeted stance-phase ankle resistance across varying force magnitudes in chronic survivors of stroke. We hypothesized that with this targeted approach, we would engage individuals’ latent propulsion reserve through ankle-specific mechanisms, such as ankle kinetics and plantarflexor muscle activity. We expected to observe after-effects of increased propulsion compared to baseline for strides immediately following removal of the resistive force, due to the trained increase in ankle use. We also posited that with increased force magnitude, we would observe greater gains in propulsion metrics following resistance, but at the cost of increased use of the unresisted proximal joints and non-paretic limb, based on our prior work in healthy individuals [28]. To control for the effects of speed on joint kinetics and kinematics, we conducted this investigation on a treadmill with fixed walking speeds for each individual. We performed one additional proof-of-concept exploratory experiment to assess the value of an exosuit for resistive training in which individuals walked on a treadmill without any active resistance to quantify improvements in propulsion solely from treadmill training.
More at link.
Tuesday, April 11, 2023
Bioliberty secures £2.2m for robotic glove for stroke rehab
If all it does is monitor then it won't do a damn thing for the 30% of survivors that have spasticity. Like me, I have zero ability to open the hand.
Bioliberty secures £2.2m for robotic glove for stroke rehab
Scottish technology firm Bioliberty has secured £2.2 million in funding to develop a soft robotic glove which can restore upper limb mobility in patients following a stroke.
JAMIE WILLIAMSON Jamie Williamson
Bioliberty
The funding round was led by Archangels, the world's longest running business angel investment syndicate, with participation from Eos Advisory, Old College Capital, and Hanna Capital SEZC.
The Edinburgh-based business has created the Lifeglov – a soft robotic glove which offers rehabilitation for both the closing and opening strength of the hand. The glove monitors key metrics related to upper limb mobility and can show improvement as the patient progresses through their rehab.
The Lifeglov is accompanied by a Digital Therapy Platform, which provides the patient with tailored exercises to help develop natural hand strength. For stroke survivors, the glove helps carry out rehabilitation from the home. For occupational therapists, the glove is a tool to help manage their patients remotely and improve patient outcomes.
The new funding will allow Bioliberty to complete development of the trial product and finalise the development of its platform. The funding is also anticipated to fund the business through obtaining FDA approval and early commercial engagement in the US with rehabilitation clinics.
In the US alone, there are more than 800,000 strokes every year, with 88% of patients left with upper limb weakness. At the same time, there is an urgent need for at-home occupational therapy services, with demand for such services forecast to outpace the supply within all 50 states of the US by 2030.
Lifeglov’s use of soft robotics in rehabilitation, which is currently unique in the market, means the product is more pliable, comfortable, and complementary to the upper arm whilst also generating useful data related to stroke recovery.
The initial application is in the upper limb rehabilitation market, but the technology could have a broad range of clinical applications including lower limb.
The business was co-founded in 2020 by Rowan Armstrong (CEO), Conan Bradley (chief design), Ross O’Hanlon (CTO) and Shea Quinn (COO) and currently employs a team of seven.
Rowan Armstrong, CEO at Bioliberty, said: “Our aim at Bioliberty is to empower every human to live a longer independent life by providing assistive robotics and rehabilitative technologies. The Lifeglov is a first step on this journey and the funding announced today will allow us to complete its development, along with our software platform, while preparing the runway for our US sales push. We’re confident in our technology and excited by the benefits it can deliver for both patients and occupational therapists.”
Niki McKenzie, joint managing director at Archangels, said: “Bioliberty has developed a highly effective solution for helping patients with hand weakness, with the potential to improve the quality of life for millions worldwide. We believe its technology has far-reaching benefits beyond this first application, providing the business with an excellent opportunity to grow quickly from its base here in Scotland. Archangels is excited to be supporting the team as they finalise what we hope will be the first of many products and start scaling up their sales activity.”
Thursday, April 6, 2023
Decoding hand and Wrist Movement Intention From Chronic Stroke Survivors With Hemiparesis Using A Wearable, User-Centric Neural Interface
Unless this has figured out a way to disrupt the signals from spasticity this is not going to help the 30% of survivors that have spasticity. Which if we had any leadership at all in stroke would have been one of the design requirements!
Decoding hand and Wrist Movement Intention From Chronic Stroke Survivors With Hemiparesis Using A Wearable, User-Centric Neural Interface
Research Objectives
To investigate the use of the NeuroLife® Sleeve to decode hand and wrist movements in chronic stroke survivors with hemiparesis for the eventual control of assistive devices. The NeuroLife Sleeve is a wearable garment worn on the forearm with 150 embedded electrodes spread across the forearm to record high-resolution surface electromyography (sEMG).
Design
Using the NeuroLife Sleeve, EMG activity was recorded while participants attempted 12 hand and wrist movements during three separate 2-hour sessions.
Setting
All studies were conducted at Battelle's laboratories. Participants were referred from therapists in the Columbus area or recruited from local support groups.
Participants
Six chronic stroke survivors (>6 months after stroke) with upper extremity motor impairment (Upper Extremity Fugl-Meyer: 7-38).
Interventions
Participants followed a series of hand and wrist movements on a computer monitor and performed the shown movement to the best of their ability.
Main Outcome Measures
EMG decoding accuracy to correctly predict movement intention from EMG data recorded from the NeuroLife Sleeve.
Results
We demonstrate that the NeuroLife Sleeve can accurately decode 12 functional hand and wrist movements, including multiple types of grasps with 75% average accuracy across subjects in simulated real-time situations. These results highlight the utility of the NeuroLife Sleeve and decoding algorithms as potential control systems for assistive devices. Collected feedback from stroke survivors who tested the system demonstrate the user centric design of the NeuroLife Sleeve, including being simple to don and doff, comfortable, portable, and lightweight.
Conclusions
The NeuroLife Sleeve represents a user centric, platform technology to record and decode high-definition electromyography for the eventual real-time control of assistive devices.
Saturday, April 1, 2023
Immediate improvements in post-stroke gait biomechanics are induced with both real-time limb position and propulsive force biofeedback
I see nothing here that suggests they are solving the spasticity problem in walking.
Since 30% of survivors that have spasticity, they are screwed in walking recovery.
Right now I have zero propulsion, the whole leg is swung from the hip
Immediate improvements in post-stroke gait biomechanics are induced with both real-time limb position and propulsive force biofeedback
Journal of NeuroEngineering and Rehabilitation volume 20, Article number: 37 (2023)
Abstract
Background
Paretic propulsion [measured as anteriorly-directed ground reaction forces (AGRF)] and trailing limb angle (TLA) show robust inter-relationships, and represent two key modifiable post-stroke gait variables that have biomechanical and clinical relevance. Our recent work demonstrated that real-time biofeedback is a feasible paradigm for modulating AGRF and TLA in able-bodied participants. However, the effects of TLA biofeedback on gait biomechanics of post-stroke individuals are poorly understood. Thus, our objective was to investigate the effects of unilateral, real-time, audiovisual TLA versus AGRF biofeedback on gait biomechanics in post-stroke individuals.
Methods
Nine post-stroke individuals (6 males, age 63 ± 9.8 years, 44.9 months post-stroke) participated in a single session of gait analysis comprised of three types of walking trials: no biofeedback, AGRF biofeedback, and TLA biofeedback. Biofeedback unilaterally targeted deficits on the paretic limb. Dependent variables included peak AGRF, TLA, and ankle plantarflexor moment. One-way repeated measures ANOVA with Bonferroni-corrected post-hoc comparisons were conducted to detect the effect of biofeedback on gait biomechanics variables.
Results
Compared to no-biofeedback, both AGRF and TLA biofeedback induced unilateral increases in paretic AGRF. TLA biofeedback induced significantly larger increases in paretic TLA than AGRF biofeedback. AGRF biofeedback increased ankle moment, and both feedback conditions increased non-paretic step length. Both types of biofeedback specifically targeted the paretic limb without inducing changes in the non-paretic limb.
Conclusions
By showing comparable increases in paretic limb gait biomechanics in response to both TLA and AGRF biofeedback, our novel findings provide the rationale and feasibility of paretic TLA as a gait biofeedback target for post-stroke individuals. Additionally, our results provide preliminary insights into divergent biomechanical mechanisms underlying improvements in post-stroke gait induced by these two biofeedback targets. We lay the groundwork for future investigations incorporating greater dosages and longer-term therapeutic effects of TLA biofeedback as a stroke gait rehabilitation strategy.
Trial registration NCT03466372
Introduction
Hemiparesis following stroke causes unilateral deficits in gait kinematics and kinetics, contributing to slowed gait speed, gait asymmetries, and increased fall risk [1,2,3]. While increasing gait speed is a major goal of stroke rehabilitation [4, 5], improvements in speed can be achieved either through restoration of paretic limb function or compensatory strategies [6]. Measurement of kinematic and kinetic gait biomechanics variables can parse out restoration versus compensation as sources of gait recovery or training-induced improvements [7]. Reduced paretic propulsion, measured as the anterior component of the ground reaction force (AGRF) generated during late stance, is an important biomechanical deficit closely associated with gait speed and walking function post-stroke [8,9,10,11]. Importantly, individuals post-stroke demonstrate a paretic propulsive reserve [12] that can be exploited using gait training interventions [13, 14], with improvements in propulsion correlating to improvements in gait speed [8]. Thus, propulsion has emerged as a key modifiable post-stroke gait variable that is biomechanically and clinically relevant.
Previous studies have demonstrated two major biomechanical gait variables that contribute to overall propulsion, ankle plantarflexor moment, and trailing limb angle [15]. Ankle plantarflexors generate most of the force required to facilitate a smooth stance-to-swing transition [16]. Trailing limb angle (TLA), a measure of the overall limb angle or position with respect to the center of mass, places the leg in a better orientation to direct ground reaction forces more anteriorly [17]. Individuals post-stroke demonstrate deficits in both paretic plantarflexor moment and TLA [15], yet increases in paretic propulsion appear to originate mainly from improvements in paretic TLA [12, 18]. Post-stroke AGRF and TLA show robust inter-relationships, indicating that TLA can be used as a surrogate for paretic AGRF measurements [19]. Taken together, these studies suggest that targeting post-stroke TLA deficits may be a feasible and effective way of improving paretic propulsion.
Real-time biofeedback has emerged as a promising post-stroke gait training strategy that can target specific gait deficits on the paretic limb [20,21,22,23]. Previously, unilateral biofeedback targeting paretic propulsion was shown to induce significant increases in paretic limb propulsion without concomitant compensatory changes in the non-paretic limb [20]. However, translation of propulsion biofeedback from laboratory to clinic remains difficult because laboratory-based instrumented walkways or treadmills needed to measure AGRF may not be clinically accessible. The use of portable and wearable AGRF sensors for gait assessment is under study and not yet clinically available [24]. Moreover, estimation of propulsion through observational gait analysis is challenging even for movement experts with considerable clinical experience [25]. In contrast, measurements of TLA do not require the use of force platforms, and can be more easily subjectively estimated by clinicians based on the relationship of the forefoot to the pelvis or greater trochanter during observational gait analysis [19]. Recently, we demonstrated that able-bodied individuals are able to modulate TLA and AGRF unilaterally in response to real-time unilateral TLA biofeedback [26]. Thus, TLA biofeedback holds promise as a clinically applicable intervention that could preferentially increase paretic AGRF and reduce post-stroke propulsion deficits. While AGRF and TLA have been studied together as outcome variables in previous research, to our knowledge, biofeedback for these 2 biomechanical targets has not been directly compared in people post-stroke. Thus, an initial assessment of the feasibility and immediate biomechanical effects of TLA biofeedback on post-stroke individuals is needed.
Here, we studied the effects of TLA biofeedback on post-stroke gait biomechanics. Moreover, to assess its use as a suitable and clinically applicable alternative to AGRF biofeedback, we compared the immediate biomechanical effects of TLA biofeedback to AGRF biofeedback. We hypothesized that a biofeedback paradigm targeting paretic TLA would elicit favorable improvements in paretic propulsion and other post-stroke gait biomechanics impairments that are comparable in magnitude to AGRF biofeedback.
More at link.
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