Peter Hurwitz

Article: Improvement of athletic performance with haptics: results of the POWER-UP Trial - The Journal of Sports Medicine and Physical Fitness 2026 March;66(3):355-61 - Minerva Medica - Journals

Introduction Acute and chronic pain affects patients’ overall health status and well-being, and the assessment and treatment of these patients can be challenging. Unfortunately, many patients fail to respond to the available multimodal treatment options, with some even failing advanced interventions including surgery. Therefore, alternative approaches to pain treatment represent an unmet medical need. Haptic vibrotactile trigger technology (VTT) is designed to target nociceptive pathways and is theorized to disrupt the neuromatrix of pain. The aim of this study was to evaluate the analgesic effects of a wearable VTT haptic patch in adults diagnosed with mild-to-moderate acute or chronic pain. Methods This was a prospective, randomized, controlled, double-blind study. A total of 118 research participants (58 male, 60 female) met the inclusion criteria and were enrolled in the study. Participants were randomly assigned to either a treatment group receiving the active patch (N = 64) or a control group which used a similar-appearing vehicle/placebo patch (N = 54). Assessments were performed at baseline (day 0), day 7, and day 14. Reduction in pain severity and interference was assessed using the validated Brief Pain Inventory (BPI), and range of motion/flexibility assessment was performed using the Schober (only for low back pain), goniometer, and bubble inclinometer tests. Data for the active patch user group and the control group were aggregated and compared over the 14-day time frame of the study. Results The active patch user group had significantly greater improvement in pain severity and reduction in pain interference; in addition, the active patch group showed greater objective improvement in range of motion (ROM)/flexibility than the control group at day 7 and day 14. Conclusion These findings suggest that this non-pharmacological, noninvasive, topical VTT haptic patch (FREEDOM Super Patch with VTT) can reduce pain severity and increase ROM/flexibility. Considering the multitude of serious adverse effects associated with standard pharmacological pain treatments, clinicians should consider this readily available, over-the-counter VTT patch as a potential first-line or adjunct therapy to treat pain. Trial Registration ClinicalTrials.gov identifier, NCT06505005.

Background: Chronic anxiety affects one-third of US adults and has increased by 6% from 2023 to 2024. Medical management is typically psychopharmacology utilizing antidepressants and/or anxiolytics and psychotherapy, but these are not always successful as treatments. Nonadherence or noncompliance to prescribed drugs for mental health disorders is common, and benzodiazepines as an anxiolytic class are also recognized as especially subject to misuse. Settings and Design: This single blinded, case-control study tested the use of a potential alternative or adjunctive treatment for anxiety of a Haptic Vibrotactile Technology patch. Methods and Materials: There were 102 adults enrolled in the study. 65 were assigned to the treatment group (TG) and 37 to the control group (CG). The TG gender ratio was 49 females/16 males; the CG gender ratio was 23 females/14 males. Two types of validated surveys were utilized, the Perceived Stress Scale (PSS) and the Short Form-20 (SF-20), and these two scaled surveys were administered at the three study intervals of Baseline, Day 7, and Day 14. Statistical Analysis Used: The numerically coded quantitative data collected were analyzed using SPSS software. Data were analyzed using paired t-tests and a two-tailed alpha level of 0.05 was used for all statistical comparisons. Results: At Day 14, there was a 31.3% difference between TG and CG for the PSS, showing marked positive effect for the TG patients as compared to the CG patients. The mean PSS score for TG patients decreased by 33%, showing a significant reduction in emotional/mental stress. For the SF-20, a positive change in the TG was shown, with a 23.8% increase in the percent score for the survey’s Mental Health domain and a notable increase for the Health Perception domain. At Day 14, >90% of the TG reported satisfaction with the patch; 90% indicated that they would recommend it. In contrast, there was little change in all PSS and SF-20 scores from baseline to Day 14 for the CG; 97.3% of the CG were not at all satisfied with the patch (which was a placebo), and only 3% reported they would recommend it. Conclusions: The overall findings of this clinical trial revealed that the studied patch (PEACE Patch with vibrotactile trigger technology [VTT]; Super Patch Company, Srysty Holding Co, Toronto, Canada) was effective in reducing anxiety symptoms. Gaining a better understanding of how the brain interacts with external stimuli, such as through VTT, may lead to the development of more viable, safe, and effective “drug-free” treatment options, which can provide adults living with chronic anxiety more potential options for relieving their symptoms and acquiring a better overall quality of life. The VTT patch utilized in this study appears to be effective in reducing anxiety symptoms and so may present an alternative or adjunct treatment modality for chronic anxiety. Further research is needed to determine if the results found in our study differ depending upon the specific adult age demographic studied, such as effectiveness in the younger, middle-aged, and senior-aged adult population, rather than across the entire adult age group spectrum, and also in adults with poststroke or post-traumatic brain injury or living with various neurodegenerative disorders.

The recent identification of Piezo ion channels demonstrating a mechano-sensitive impact on neurons revealed distinct Piezo-1 and 2 types. While Piezo-1 predominates in neurons linked to non-sensory stimulation, such as pressure in blood vessels, Piezo-2 predominates in neurons linked to sensory stimulation, such as touch. Piezo-1 and 2 have a major bidirectional impact on transient receptor potential (TRP) ion channels, and TRPs also impact neurotransmitter release. Particularly existent in dorsal root ganglion (DRG) neurons, which are located in nerve endings, Piezo-2 is a key DRG activator. Subsequent Piezo findings have been vital to recent medical haptic technology developments, in tandem with breakthroughs in the emerging neurology subfield of connectomics plus AI developments. Included in this review are a historical Piezo overview, the interrelationship of Piezo channels with TRPs, inclusive of TRPV1/TRPV8, the impact on medical and rehab haptic technology, a focus on haptic technology use in stroke survivor rehab inclusive of pain mitigation, and the development of a haptic technology patch aimed at alleviating pain and/or anxiety. Neurogenic pain resulting from hyperalgesia/allodynia in stroke survivors is a potential target for drugs and haptics aimed at pain reduction; patients experiencing neuropathic or psychosomatic pain are other prime targets. Increased Piezo knowledge may promote more precisely targeted haptic therapeutic developments.

The conceptual framework of cognitive networks, or cognits, represents a system of working memory, especially long-term memory arrays that are intrinsically designed to attain certain behavioral ends and that are activated by a neural structure. Despite the fact that cognitions can be used in a plethora of systems, current technologies allow manipulations of the central nervous system (CNS) to execute certain sensory and motor functions. Sensation and tactual perception by the skin are an innate mechanism for human survival and represent our adaptive somatosensorial ability to apprehend information via haptics—the active touch for object recognition and perception by higher centers of the brain. The somatosensation, which is identified by a set of channels and receptors sensitive to a variety of stimuli (thermal, tactile, and mechanical), is critical to survival, balance control, cognition, and pain modulation. Cognits are cutting-edge tools and modalities that provide a landscape of theoretical assets, evidencebased experimental protocols, computational intelligence schemes, and direct empirical modalities that facilitate the understanding of the complex functionalities of the human brain. By evaluating neuroimaging data after somatosensory stimulation and collected via electroencephalogram (EEG), cognition response and change can be obtained that allows researchers to gain a better understanding of emerging scientific approaches aimed at understanding human behavioral outcomes. An emerging technology, haptic vibrotactile trigger technology (VTT), incorporates somatosensory patterns in compression sleeves. eSmartr Smart Compression Sleeves (Srysty Holdings Inc., Mississauga, ON, Canada) with VTT and its Cognitive Boost Technology (CBT) pattern is designed to optimize neural communications for improved mindful wellness. This technology has also been incorporated into patches, braces, apparel (socks), wrist bands, and other routes of delivery. Mindful wellness is considered an outcome of somatosensory intervention that modulates the behavioral responses associated with cognitive networks. Currently, there is limited research exploring these modalities, exposing the need to study new technologies and their influence on somatosensory pathways and cognitive networks. The purpose of this IRB-approved study was to explore the effects of forearm VTT stimulation patterns on cognitive networks by comparing a baseline EEG to an EEG after placing a sleeve incorporating VTT on the right or left forearm of adult healthy individuals. Materials and methods: A baseline EEG was recorded over 5 minutes from 19 scalp locations on 20 subjects ranging in age from 17.6 years to 41.9 years (n=7 females, 13 males). The subject’s dominant arm was then fitted with the eSmartr Smart Compression Sleeve for 20 minutes and another 5-minute EEG was recorded. Both the LORETA (Low Resolution Electromagnetic Tomography Analysis) inverse solution and a power spectral analysis of the surface EEG were calculated. Additionally, for 10 distinct networks, the current sources from 88 Brodmann areas were computed. The variables were absolute power and absolute current density in 1 Hz increments in 10 frequency bands (delta, theta, alpha-1, alpha-2, beta-1, beta-2, beta-3, and hi-beta). Paired t-tests were computed for each individual for all EEG parameters, as well as group paired t-tests, between the baseline EEG and followup EEG. Results: The results showed statistically significant t-test differences (P < 0.01) in both the surface EEG and the LORETA current sources between the baseline measurement and the follow-up ‘sleeve-on’ measurement. The largest differences were detected with a prominent downregulation of alpha and beta frequency powers at both the surface EEG and the LORETA current sources with the “sleeve-on,” as compared to baseline. In addition, the maximal effects of the “sleeve-on” condition were in the left frontal and left temporal surface EEGs and on the medial bank of the somatosensory cortex in the range of the alpha frequency. Changes in the default network and attention network were also prominent. Conclusions: Study results indicate that these non-pharmacologic, non-invasive, haptic vibrotactile trigger technology (VTT) patterned compression sleeves elicited a response in multiple cognitive networks. These networks play a key role in executive function, memory, attention, mood, and information flow. There was a prominent effect of the haptic vibrotactile trigger technology with the CBT- patterned sleeves on the EEG that was primarily located in alpha and beta frequency bands. The substantial impacts on the homuncular projection of the arm to the medial somatosensory cortex as well as the default network demonstrated activity influenced by the patterned sleeve. The mechanisms of action of the VTT sleeve on the brain, neuropathways, and the EEG spectrum are still being investigated. If results are confirmed with further research, this novel VTT technology could be a promising addition as a non-invasive and non-drug treatment approach for a variety of conditions and therapeutic applications.

Motivation: Biomarker discovery is one of the most frequent pursuits in bioinformatics and is crucial for precision medicine, disease prognosis, and drug discovery. A common challenge of biomarker discovery applications is the low ratio of samples over features for the selection of a reliable not-redundant subset of features, but despite the development of efficient tree-based classification methods, such as the extreme gradient boosting (XGBoost), this limitation is still relevant. Moreover, existing approaches for optimizing XGBoost do not deal effectively with the class imbalance nature of the biomarker discovery problems, and the presence of multiple conflicting objectives, since they focus on the training of a single-objective model. In the current work, we introduce MEvA-X, a novel hybrid ensemble for feature selection (FS) and classification, combining a niche-based multiobjective evolutionary algorithm (EA) with the XGBoost classifier. MEvA-X deploys a multiobjective EA to optimize the hyperparameters of the classifier and perform FS, identifying a set of Pareto-optimal solutions and optimizing multiple objectives, including classification and model simplicity metrics. Results: The performance of the MEvA-X tool was benchmarked using one omics dataset coming from a microarray gene expression experiment, and one clinical questionnaire-based dataset combined with demographic information. MEvA-X tool outperformed the state-of-the-art methods in the balanced categorization of classes, creating multiple low-complexity models and identifying important nonredundant biomarkers. The best-performing run of MEvA-X for the prediction of weight loss using gene expression data yields a small set of blood circulatory markers which are sufficient for this precision nutrition application but need further validation. Availability and implementation: https://github.com/PanKonstantinos/MEvA-X.

Purpose: Pain is the most common reason for patients to consult primary care providers. Identification of effective treatments with minimal adverse events is critical to safer opioid-sparing and multi-modal approaches to pain treatment. Topical analgesic patches target medication to peripheral sites of pain while potentially avoiding adverse effects associated with systemic medications. Opioids, prescription nonsteroidal anti-inflammatory drugs, and over-the-counter oral medications are associated with systemic toxicities, increasing morbidity and mortality. This study evaluated a topical analgesic pain-relieving patch in reducing pain severity and improving function in patients with mild to moderate arthritic, neurological, or musculoskeletal pain. Patients and Methods: This Institutional Review Board-approved study evaluated the effectiveness of a topical pain-relieving patch in reducing Brief Pain Inventory (BPI) scores in patients. The treatment group (TG) (n=152) received patches for 14 days. A control group (CG) (n=47) did not receive the patch. After day 14, 34 CG patients crossed over to treatment (CROSSG) with the patch. Surveys were administered to patients at baseline and 14 days to assess changes in pain severity and interference. Changes in oral pain medication use, side effects, and satisfaction use were also assessed. Results: Paired data were collected in the CG, TG and CROSSG. At day 14, TG pain severity score and pain interference score decreased (49% and 58.1%, respectively). Pain severity and interference scores decreased less in the CG (12.3% and 14.8%, respectively). In the study, 60.5% of the TG were using concomitant oral pain medications “a lot less”, and 90.8% were very/extremely satisfied with the patch. CROSSG patients showed similar reductions in pain severity and interference scores after patch treatment. No side effects of treatment were reported. Conclusion: Results indicate that this topical analgesic pain-relieving patch can reduce BPI pain severity and interference scores in adult patients with mild to moderate arthritic, neurological, and musculoskeletal pain and should be considered as a treatment option.

Purpose: Chronic pain is a life changing condition, and non-opioid treatments have been lately introduced to overcome the addictive nature of opioid therapies and their side effects. In the present study, we explore the potential of machine learning methods to discriminate chronic pain patients into ones who will benefit from such a treatment and ones who will not, aiming to personalize their treatment. Patients and Methods: In the current study, data from the OPERA study were used, with 631 chronic pain patients answering the Brief Pain Inventory (BPI) validated questionnaire along with supplemental questions before and after a follow-up period. A novel machine learning approach combining multi-objective optimization and support vector regression was used to build prediction models which can predict, using responses in the baseline, the four different outcomes of the study: total drugs change, total interference change, total severity change, and total complaints change. Data were split to training (504 patients) and testing (127 patients) sets and all results are measured on the independent test set. Results: The machine learning models extracted in the present study significantly overcame other state of the art machine learning methods which were deployed for comparative purposes. The experimental results indicated that the machine learning models can predict the outcomes of this study with considerably high accuracy (AUC 73.8– 87.2%) and this allowed their incorporation in a decision support system for the selection of the treatment of chronic pain patients. Conclusion: Results of this study revealed the potential of machine learning for an individualized medicine application for chronic pain therapies. Topical analgesics treatment were proven to be, in general, beneficial but carefully selecting with the suggested individualized medicine decision support system was able to decrease by approximately 10% the patients which would have been subscribed with topical analgesics without having benefits from it.

Background: Opioids and other controlled substances prescribed for chronic pain are associated with abuse, addiction, and death, prompting national initiatives to identify safe and effective pain management strategies including topical analgesics. Methods: This prospective, observational study evaluated changes from baseline in overall mean severity and interference scores on the Brief Pain Inventory scale and the use of concurrent pain medications at 3- and 6-month follow-up assessments in chronic pain patients treated with topical analgesics. Changes in pain severity and interference and medication usage were compared between treated patients and unmatched and matched controls. Results: The unmatched intervention group (unmatched-IG) included 631 patients who completed baseline and 3-month follow-up surveys (3-month unmatched-IG) and 158 who completed baseline and 6-month follow-up assessments (6-month unmatched-IG). Baseline and 3-month follow-up data were provided by 76 unmatched controls and 76 matched controls (3-month unmatched-CG and matched-CG), and 51 unmatched and 36 matched patients completed baseline and 6-month follow-up surveys (6-month unmatched-CG and matched-CG). Baseline demographic characteristics and mean pain severity and interference scores were similar between groups. There were statistically significant decreases from baseline in mean pain severity and interference scores within the 3- and 6-month unmatched-IG (all PP PConclusion: Topical analgesics appear to be effective and safe for the treatment of chronic pain, with randomized controlled trials needed to confirm these findings.