Tuesday, March 31, 2026
Sunday, March 29, 2026
Stroke rehab goes high-tech: UP study reveals robotic therapy may restore lost grip
Come back when you finish the job correctly! Will restore using these EXACT PROTOCOLS! 'May' is not a valid result!
What will you do about those like me that have dead brain there and no longer have any signals coming thru? Do you actually have any brains at all that might be useful in solving stroke to 100% recovery?
Stroke rehab goes high-tech: UP study reveals robotic therapy may restore lost grip
MARCH 29, 2026 — The University of the Philippines has just dropped a study that could change how we look at stroke recovery in the country. Researchers Micah Angelo Bacani and Manuel Ramos Jr. from UP Diliman’s Electrical and Electronics Engineering Institute tested a robotic hand orthosis powered by surface electromyography (sEMG) signals — and achieved an impressive 86% response accuracy rate. In plain language: the device listens to muscle signals from the arm and translates them into movement, giving stroke survivors a shot at regaining control of their grip.
Why does this matter? Stroke remains one of the leading causes of disability in the Philippines. Many survivors struggle with long-term loss of hand function, making everyday tasks — from holding a spoon to signing a document — frustratingly difficult.
Traditional rehab often relies on repetitive, passive exercises. But this study argues that recovery is stronger when patients actively participate, engaging their neurological pathways rather than just following preset motions.
That’s where robotics step in: machines that respond to the patient’s own muscle signals, not just programmed routines.
The researchers explained, “Using surface electromyography (sEMG) signals from the arm, the recovering stroke patient can control the robotic assistive device for rehabilitation. This is the myoelectric hand orthosis.”
Additionally, the study found a direct, proportional relationship between the patient’s intended force and the device’s response. In other words, the harder the patient tries, the stronger the orthosis reacts.
Now, that’s not just science — it’s empowerment. Imagine the psychological boost of seeing your effort instantly translated into movement, instead of waiting months for uncertain progress.
Of course, this raises bigger questions for us. Will our healthcare system embrace robotic rehab, or will it remain locked in academic journals? Can public hospitals afford such technology, or will it be another innovation reserved for private clinics and the wealthy? And most importantly, will patients trust machines to help them heal?This study is a reminder that science is racing ahead, but policy and accessibility often lag behind. If robotics can truly help stroke survivors reclaim their independence, then the challenge is no longer technological — it’s social, economic, and political.
When machines can help us heal, will the Philippines let technology be a lifeline for the many, or a luxury for the few?
Poststroke Fatigue: An Overlooked Barrier to Functional Recovery
Oh for fucks sake; stop writing this crapola and just solve fatigue! Oh, you don't have the brainpower to do that simple task? Then go back to playing in your sandbox and let the adults work at it!
Let's see how long everyone in stroke has been incompetent at this problem!
- post stroke fatigue
(58 posts to January 2018)
At least half of all stroke survivors experience fatigue Known since March 2017
Or is it 70%? Known since March 2015.
Or is it 40%? Known since September 2017.
I'd fire everyone involved with this lazy crapola!
Will your incompetent doctor, hospital and board of directors fail to deliver the action needed to solve this problem? NOT DOING SO IS COMPLETE FUCKING INCOMPETENCE!
Poststroke Fatigue: An Overlooked Barrier to Functional Recovery
Despite the significance of PSF, poststroke rehabilitation strategies continue to focus on conspicuous impairments, such as sensory, motor, cognitive, and speech deficits, while overlooking fatigue and its detrimental impact on recovery.5, 6 In this commentary, we assert that PSF must be recognized and prioritized as a core component of poststroke rehabilitation. To build this argument, we highlight emerging evidence on the impact of PSF on recovery, examine the reasons for its continued neglect, and advocate for its integration into rehabilitation frameworks as a crucial step toward improving functional recovery after stroke.
PSF HINDERS FUNCTIONAL CAPACITY AND RECOVERY AFTER STROKE
PSF is a multidimensional phenomenon2 that significantly impairs functional recovery after stroke.7 PSF reduces patient engagement in rehabilitation, which is essential for effective recovery.8 Individuals experiencing PSF are more likely to miss therapy sessions, exhibit reduced ability to actively participate in rehabilitation protocols,9 and report insufficient energy to complete home‐based exercises.10 PSF also increases the need for prolonged rest10 and reduces participation in cognitively, emotionally, or physically demanding tasks.11 As a result, PSF limits workforce reintegration,12 restricts social participation, and directly stalls functional gains, often leading to more frequent and prolonged hospitalizations.7
Even when individuals participate in rehabilitation, PSF affects physical and cognitive domains essential to the rehabilitation process.13 Fatigue impairs motor control by reducing movement accuracy, increasing force variability, and slowing reaction time.13, 14, 15, 16 For example, Hyngstrom et al. found that PSF diminishes hip flexor strength and gait stability,14 and other studies link PSF to impaired lower limb control15 and slower movement speed.13 These motor deficits translate into greater difficulty performing activities of daily living,17 which in turn hinder recovery and quality of life. Further, PSF can interfere with motor learning,11 the fundamental process underlying neurorehabilitation. Stroke rehabilitation relies on repeated, high‐quality practice to drive motor skill acquisition and memory consolidation.18 However, Branscheidt et al. demonstrated that physical fatigue impairs both processes in healthy adults, raising serious concerns about the impact of fatigue in clinical populations.11 Although the effect of PSF on motor learning after stroke has yet to be fully investigated, it is plausible that fatigue directly impairs learning or indirectly reduces training efficiency, thus diminishing functional recovery after stroke. Lastly, PSF reduces attention, planning, and capacity to retain the information, making it difficult to perform cognitive tasks, but also to integrate feedback and error monitoring during rehabilitation.19, 20
Taken together, PSF undermines recovery by limiting rehabilitation engagement and impairing both physical and cognitive function. Yet despite its profound impact, fatigue remains overlooked and underprioritized in rehabilitation. In the next section, we examine why this may be the case.
WHY PSF REMAINS UNDERPRIORITIZED IN STROKE REHABILITATION?
We argue that PSF remains underrecognized and undertreated in stroke rehabilitation due to its broad definition21 and poor operationalization,22, 23 its misinterpretation as a mere consequence of other psychiatric conditions2, 24 or the recovery process,2, 24 and the stigmatization of fatigue within rehabilitation settings.25
How we define and conceptualize fatigue remains a central obstacle to addressing it effectively. Clinically, PSF is evaluated exclusively via self‐reported measures that combine all aspects of fatigue into a single score23, 26; whereas scientifically, different operationalizations of fatigue are used interchangeably.3, 6 We posit that this lack of conceptual clarity leads to inconsistent results that prevent us from understanding the prevalence, behavioral presentation, mechanisms, and functional consequences of fatigue, ultimately hindering the development of effective clinical interventions.27, 28
In addition, fatigue is commonly interpreted as an inevitable consequence of the rehabilitation process itself10 or a simple byproduct of psychiatric conditions,29 such as depression, poor sleep, or anxiety. Yet accumulating evidence suggests that fatigue can be a distinct causal factor6 that independently contributes to poor functional performance and impairs recovery.3, 8, 11, 13, 14, 15, 16, 17, 30, 31, 32 For example, in major depressive disorders, fatigue is among the most reported symptoms,30 often precedes the onset of depressive episodes,31 and strongly predicts relapses after treatment.33 A similar scenario may hold for PSF, which could act as a prodromal symptom and an independent driver of functional decline. Supporting this, Ingles et al. found that fatigue impaired mobility after stroke, even after controlling for depression.32
Finally, the neglect of fatigue is compounded by the siloed nature of clinical care and scientific inquiry, where PSF is rarely integrated into rehabilitation frameworks.27 Historically, rehabilitation models have prioritized hemiparesis, cognitive decline, or aphasia. In contrast, fatigue is dismissed as a vague, subjective, and secondary complaint that should be endured rather than treated.34 This perception has led to stigma, making it difficult for patients to convey the severity of their fatigue and for clinicians to view it as anything other than inevitable or peripheral to recovery.10 Similarly, in research settings, fatigue is often dismissed as noise or a confound to be controlled for. Consequently, fatigue research has been segregated from traditional rehabilitation sciences, reinforcing the false belief that fatigue is unmeasurable, untreatable, and unworthy of investigation.3, 6
Taken together, these barriers contribute to a limited understanding of PSF and undermine efforts to address it as a distinct and treatable symptom of stroke survivors. To break this cycle, clinicians and researchers must redefine PSF as a core barrier to recovery that warrants clinical and scientific attention. Importantly, doing so requires greater conceptual clarity. Therefore, we must first establish what PSF is and, importantly, what it is not, to distinguish it from other comorbidities, identify its unique features, and target it more effectively in both clinical practice and research.
PROPOSED FEATURE‐BASED FRAMEWORK TO CONCEPTUALIZE PSF
To move beyond the historical neglect of PSF, the field must establish a clear, shared definition of PSF and distinguish it from other comorbidities. Our central premise is that in response to the multidimensional nature of PSF, the field has collapsed distinct features of fatigue into a single, imprecise construct. As a consequence, clinically, fatigue is evaluated almost exclusively using self‐reported measures that combine multiple aspects of fatigue into a single score,23, 26 whereas, scientifically, different operationalizations of fatigue are often used interchangeably.3, 6 These approaches limit our ability to identify the neurobiological mechanisms that give rise to PSF and hinder the development of effective treatments. In an important step toward addressing this problem, Kluger et al. highlighted that fatigue comprises 2 main features, namely “perceptions of fatigue” and “performance fatigability,” and argued that these should not be used interchangeably.3 Although this framework has been highly informative, we argue that it remains incomplete.
Here, we propose to operationalize PSF along 4 distinguishable features that can co‐occur but need not covary16, 35 (Figure): (1) perceived effort (ie, how one perceives a previously exerted action; retrospective), (2) subjective feelings of tiredness (ie, how tired one feels), (3) reduced likelihood to exert effort (ie, an individual's decision to engage in effortful actions; prospective), and (4) decrements in performance (ie, fatigability3). Unlike traditional approaches, each feature should be assessed using dedicated tools. Ratings or ecological momentary assessment can capture perceived effort and subjective feelings of tiredness; effort‐based decision paradigms can quantify an individual's likelihood of exerting effort16, 36; and objective changes in accuracy, variability, or reaction time can index decrements in performance. Operationalizing fatigue through these features could help us move beyond descriptive accounts and toward mechanistic explanations of PSF.
We further encourage integrating these behavioral features with neurophysiological (eg, electromyography/electromyography/ECG/heart rate variability) and neuroimaging (eg, magnetic resonance imaging) measures to identify feature‐specific mechanisms and candidate biomarkers of PSF. Our working hypothesis is that each feature is supported by distinct neurobiological systems.16 Specifically, we hypothesize that (1) a sensorimotor network, involving the posterior insula, primary motor and sensory cortices, as well as the cerebellum, underpins perceived effort; (2) an affective network, involving the ventral anterior insula and other limbic regions, underpins subjective feelings of tiredness; (3) a decision‐making/valuation network, involving the ventral striatum and the ventromedial prefrontal cortex, underpins effort‐based decision‐making; and (4) task‐specific networks, in either the cognitive or physical domains, will underpin performance.
Within this framework, a critical unanswered question is how stroke interacts with the proposed feature‐specific mechanisms of fatigue. We posit that stroke can influence these systems via 2 complementary ways. First, the primary lesion may directly disrupt the neuroanatomical networks that support individual features.37 Damage to sensorimotor, affective, valuation, or task‐specific networks may disrupt the function of these networks, resulting in a maladaptive behavioral presentation of fatigue that is directly informed by the location of the lesion. Second, stroke may induce a broader allostatic response38, 39 in which lesion‐induced dyshomeostasis across neurophysiological systems drives persistent regulatory signaling.2 In this scenario, PSF may emerge not only from focal structural damage but also as a feedback signal arising from ongoing efforts to restore internal equilibrium and promote energy conservation, rest, and recovery. Importantly, these mechanisms are not mutually exclusive and may converge to produce similar behavioral manifestations of PSF. Future studies should therefore investigate whether PSF reflects direct neural disruption, systemic feedback signaling in response to homeostatic challenge, or a combination of both. Understanding how these mechanisms interact is essential for explaining why fatigue persists after stroke and why it remains a prominent barrier to recovery.
Finally, our central premise is that the proposed feature‐based approach will enable clinicians and researchers to more precisely characterize how PSF manifests, distinguish it from other comorbidities, and target it as a primary outcome of rehabilitation. For example, disproportionate increases in perceived effort and reduced willingness to exert effort despite preserved motor performance would be consistent with a central regulatory signal rather than primary neuromuscular weakness. In contrast, isolated decrements in performance accompanied by stable effort ratings and preserved willingness to exert effort would point toward neuromuscular fatigability or weakness. By assessing PSF at the level of its constituent features, an apparently intangible symptom can be transformed into a set of quantifiable, mechanistically interpretable components that can be meaningfully integrated into both clinical practice and research.
CALL TO ACTION: INTEGRATING PSF INTO STROKE REHABILITATION
Given its profound impact on recovery, PSF must be systematically addressed as a core component of stroke rehabilitation. To achieve this, we propose 3 key priorities. First, we should reframe PSF as a primary, persistent symptom that warrants direct clinical and scientific attention. We should no longer dismiss it as a secondary complaint or an inevitable byproduct of rehabilitation. Clinicians should proactively educate patients and caregivers about the prevalence, consequences, and management of PSF. This shared understanding could help align expectations, incorporate fatigue into rehabilitation goals, and guide the development of personalized fatigue management strategies. Similarly, rehabilitation scientists must directly integrate PSF into core research questions rather than treating it as a confound that must be controlled for. More research is needed to clarify how fatigue manifests after stroke, as well as its effects on motor and cognitive function. Experimental and clinical studies that explicitly target fatigue might enable the identification of mechanistic pathways, improve the design of therapeutic interventions, and generate evidence‐based strategies for addressing PSF in rehabilitation settings. We propose that only by simultaneously advancing both the clinical and scientific approaches to PSF can we fully understand and address the barriers that fatigue imposes on poststroke recovery.
Second, rather than collapsing fatigue into a single self‐reported score, PSF could, and we argue should, be measured with a multidimensional battery that separately captures its different features. When feasible, these behavioral indices can be paired with physiological recordings to identify candidate biomarkers of PSF. The development and use of this strategy could result in feature‐based subscores that (1) track trajectories across subacute and chronic phases, (2) reveal individual differences of relative prominence for each feature, and (3) support patient stratification into actionable phenotypes (eg, effort sensitive, fatigability dominant, tiredness dominant, or mixed). Crucially, each phenotype could imply distinct intervention strategies. For example, sensorimotor recalibration and feedback optimization for elevated perceived effort, autonomic regulation strategies for pronounced tiredness, contingency‐based scheduling for effort‐averse decision profiles, and targeted strengthening/aerobic conditioning for predominant fatigability. Characterizing PSF in this way may not only advance science but also transform clinical practice, ensuring fatigue is no longer overlooked but systematically measured, targeted, and followed as a core outcome of recovery after stroke.
Lastly, we may not accomplish these priorities without a multidisciplinary approach to PSF. Collaboration among neurologists, rehabilitation specialists, psychologists, researchers, and, importantly, patients will accelerate understanding, facilitate the development of validated assessment tools, and lead to the establishment of effective, evidence‐based treatments. We propose that such a coordinated approach is essential to shift the current paradigm of stroke care to a more holistic model that addresses inconspicuous yet debilitating symptoms like fatigue. By prioritizing awareness, measurement, and collaboration, we can meaningfully integrate PSF into rehabilitation frameworks and improve long‐term recovery outcomes and quality of life for stroke survivors.
CONCLUSIONS
PSF is not just a vague, secondary symptom that must be pushed through—it is a measurable, mechanistically driven, and clinically significant barrier to recovery after stroke. Yet, continuing to overlook it perpetuates poor quality of life, stalls functional gains, and undermines the central goals of rehabilitation. The scientific understanding and tools to address PSF are already within reach; what remains missing is widespread recognition and coordinated action. By redefining how we conceptualize, measure, and manage fatigue, we can establish PSF as a core target of stroke rehabilitation, at par with motor, cognitive, and speech impairments. To us, the path forward is clear: it is time to stop dismissing fatigue and start treating it as an integral component of stroke recovery.
Sources of Funding
This work was supported by the National Institutes of Health (K01AG070327 to Neha Lodha) and (R00NS133961 to Agostina Casamento‐Moran).
Footnotes
The opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.
This article was sent to Jose R. Romero, MD, Associate Editor, for review by expert referees, editorial decision, and final disposition.
For Sources of Funding and Disclosures, see page 5.
Split Protein Builds the Infrastructure for Weight Loss
My doctor obviously knew nothing about weight gain post stroke. He didn't reference body metabolism slowing down after age 50 and my limited exercise ability which I used to do to excess allowing me to eat as I wanted. This incompetence led me to a 30 lb. weight gain which I'm still working to conquer.
Will your competent? doctor and hospital at least get research going that delivers EXACT PROTOCOLs TO INITIATE THIS?
Do you prefer your doctor, hospital and board of director's incompetence NOT KNOWING? OR NOT DOING? Your choice; let them be incompetent or demand action!
Split Protein Builds the Infrastructure for Weight Loss
Summary: While current weight-loss blockbusters like GLP-1s focus on suppressing appetite, researchers have uncovered a completely different strategy: increasing energy expenditure by “building out” the body’s natural heat-generating tissue.
The study reveals how a protein called SLIT3 acts as a “split signal” to grow the essential nerve and blood vessel networks within brown fat. Without this infrastructure, brown fat cannot receive the brain’s “get warm” signals or the nutrients it needs to burn calories. This discovery suggests that obesity could be treated by enhancing the body’s internal “metabolic sink” rather than just eating less.
Key Facts
- The “Split Signal”: When brown fat cells secrete SLIT3, an enzyme called BMP1 cleaves it into two fragments. One fragment grows the blood vessels (supplying fuel), while the other expands the nerves (supplying the “on” switch).
- The Metabolic Sink: Activated brown fat acts as a “sink,” drawing in glucose and lipids from the bloodstream to generate heat (thermogenesis) instead of storing them as white fat.
- The PLXNA1 Receptor: Researchers identified PLXNA1 as the specific docking station for SLIT3 that controls nerve density. Mice lacking this receptor couldn’t maintain their body temperature in the cold because their brown fat lacked the “wiring” to hear the brain’s signals.
- Human Evidence: Analyzing fat samples from over 1,500 people, the team found that SLIT3 gene expression is closely linked to metabolic health, inflammation, and insulin sensitivity in individuals with obesity.
Source: NYU
Researchers have determined how a key protein activates brown fat by expanding blood vessels and nerves in the heat-generating tissue.
The findings, published in Nature Communications, point to a potential strategy for treating obesity that deviates from the current approach of suppressing appetite.
Most of the fat in our bodies is white fat, which stores excess energy and, at too high of levels, can lead to obesity. Humans and other mammals also have a smaller amount of brown fat, a specialized tissue that regulates body temperature and is closely linked to weight loss and metabolic health. When activated by exposure to cold, brown fat uses the body’s resources like glucose and lipids to generate heat, a process called thermogenesis.
“During thermogenesis, all of that chemical energy is dissipated as heat instead of being stored in the body as white fat,” said Farnaz Shamsi, assistant professor of molecular pathobiology at NYU College of Dentistry and the study’s senior author.
“By rapidly taking up and using fuel sources from our bodies and the food that we eat, brown fat acts like a metabolic sink that draws in nutrients and prevents them from being stored.”
Brown fat has intricate, dense networks of nerves and blood vessels that are critical for its functioning. Nerves enable brown fat to communicate with the brain; when the brain senses cold, it rapidly signals to activate brown fat.
Blood vessels supply brown fat with oxygen and nutrients to generate heat, and then distribute this heat throughout the body. While research on brown fat has largely focused on stimulating fat cells to generate heat, less is known about how these underlying networks function.
Shamsi’s lab previously used single-cell RNA sequencing to identify SLIT3, a protein secreted by brown fat cells, which they thought may play a role in how fat cells communicate. When produced, SLIT3 gets cleaved into two different fragments.
In the Nature Communications study, using a combination of approaches in human and mouse cells, the researchers discovered the enzyme, BMP1, that is responsible for cleaving SLIT3 into two. They also determined that the two SLIT3 fragments control different processes: one grows the network of blood vessels, while the other expands the network of nerves.
“It works as a split signal, which is an elegant evolutionary design in which two components of a single factor independently regulate distinct processes that must be tightly coordinated in space and time,” noted Shamsi.
In addition, the researchers identified the receptor, PLXNA1, that binds to one of the SLIT3 fragments to control brown fat’s network of nerves. In studies in mice—which typically have very active brown fat and can tolerate cold temperatures for long periods of time—removing SLIT3 or the PLXNA1 receptor from brown fat resulted in mice becoming sensitive to cold and having difficulty maintaining their body temperatures. A closer look at brown fat tissue missing SLIT3 or its receptor revealed that it lacks the proper nerve structure and density of blood vessels.
To see if their findings translate to humans, the researchers examined samples of fat tissue from more than 1,5000 people, some of whom had obesity. Focusing on the gene that produces SLIT3, which prior studies show is associated with obesity and insulin resistance, they found that SLIT3 gene expression may regulate fat tissue health, inflammation, and insulin sensitivity in people with obesity.
“That really got our attention, as it suggests that this pathway could be relevant in human obesity and metabolic health,” said Shamsi.
While most weight loss drugs—including GLP-1s—suppress appetite, decreasing the amount of food people eat and therefore the amount of energy stored, treatments that involve brown fat have the potential to increase energy expenditure.
This new understanding of what’s happening inside brown fat—including how SLIT3 splits into two and binds to receptors to control nerves and blood vessels—highlights several processes that could potentially be harnessed for their therapeutic potential.
“Our research shows that just having brown fat isn’t enough—you need the right infrastructure within the tissue for heat production,” said Shamsi.
Additional study authors include Tamires Duarte Afonso Serdan, Heidi Cervantes, Benjamin Frank, Akhil Gargey Iragavarapu, Qiyu Tian, Daniel Hope, and Halil Aydin of NYU College of Dentistry; Chan Hee Choi and Paul Cohen of Rockefeller University; Anne Hoffmann and Matthias Blüher of the University of Leipzig; Adhideb Ghosh and Christian Wolfrum of ETH Zurich; Matthew Greenblatt of Weill Cornell Medical College; and Gary Schwartz of Albert Einstein College of Medicine.
Funding: The research was supported in part by the National Institutes of Health (K01DK125608, R03DK135786, R01DK136724, RC2DK129961, R35GM150942), the G. Harold and Leila Y. Mathers Charitable Foundation, the American Heart Association (24CDA1271852), the Einstein-Mount Sinai Diabetes Center, the NYU Dentistry Department of Molecular Pathobiology, and the Boettcher Foundation.
Key Questions Answered:
Q: If I have brown fat, why am I not losing weight automatically?
A: As senior author Farnaz Shamsi points out, “just having brown fat isn’t enough.” If your brown fat doesn’t have the right “infrastructure”—meaning enough nerves to hear the brain’s signals and enough blood vessels to get oxygen—it stays dormant. It’s like having a high-performance engine with no fuel line or ignition switch.
Q: How is this different from drugs like Ozempic or Wegovy?
A: Most current drugs (GLP-1s) work by telling your brain you aren’t hungry, which reduces the energy going in. This SLIT3 pathway is about increasing the energy going out. By “upgrading” your brown fat, you are essentially turning up your body’s internal thermostat to burn through stored white fat and blood sugar.
Q: Does this mean we can “grow” more weight-loss tissue?
A: We may not need to grow more brown fat, but rather optimize what we already have. By harnessing the SLIT3-PLXNA1 pathway, scientists hope to develop therapies that “renovate” existing brown fat, making it more efficient at drawing in and burning off excess nutrients.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- Journal paper reviewed in full.
- Additional context added by our staff.
About this neurology and aging research news
Author: Rachel Harrison
Source: NYU
Contact: Rachel Harrison – NYU
Image: The image is credited to Shamsi Lab, NYU College of Dentistry
Original Research: Open access.
“SLIT3 fragments orchestrate neurovascular expansion and thermogenesis in brown adipose tissue” by Tamires Duarte Afonso Serdan, Heidi Cervantes, Benjamin Frank, Akhil Gargey Iragavarapu, Qiyu Tian, Daniel Hope, Chan Hee J. Choi, Anne Hoffmann, Adhideb Ghosh, Christian Wolfrum, Matthew B. Greenblatt, Paul Cohen, Matthias Blüher, Halil Aydin, Gary J. Schwartz & Farnaz Shamsi. Nature Communications
DOI:10.1038/s41467-026-70310-9
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