Hasil untuk "Therapeutics. Pharmacology"

O. A. Saygina, T. S. Sukhinina, M. A. Terenicheva et al.

Aim. To study the safety of using the intravenous beta-blocker (BB) esmolol in the early stages of ST-segment elevation myocardial infarction (STEMI) before primary percutaneous coronary intervention (PCI) based on an analysis of the incidence and clinical significance of adverse events (acute heart failure, hypotension, bradycardia, disorders of atrioventricular conduction (AV conduction), etc.) compared with the control group.Material and methods. The presented study is part of the randomized controlled trial ESMO-VASCMI (ClinicalTrials.gov NCT number 06376630) on the study of the cardioprotective effect of IV BB esmolol in the early stages of STEMI. The study included 121 patients (n=60 in the control group and n=61 in the esmolol group) with STEMI in the first 48 hours after the onset of symptoms contraindications to BB, who were not prescribed metoprolol before PCI due to safety concerns. The administration of esmolol began with a loading dose of 500 mcg/kg for 1 minute, followed by an infusion for 6 hours. With the development of adverse events, esmolol therapy was discontinued prematurely or temporarily suspended.Results. No statistically significant difference was observed in the frequency of adverse events potentially provoked by β1‑blocker administration between the study groups. In the esmolol group, there was a trend toward a higher incidence of bradycardia during PCI (18.03% vs 6.63%, p=0.058); hypotension (down to 70/40 mm Hg) was observed in 2 patients (3.3%), and AHF manifestations in 2 (3.3%). In 4 patients (7%), the infusion was prematurely discontinued, and in 8 (13%) it was temporarily suspended and resumed after hemodynamic stabilization. No cases of bronchospasm were detected. All cases of bradycardia and hypotension were clinically insignificant. Bradycardia developed during reperfusion with PCI, atropine was administered to 2 patients, and esmolol infusion was subsequently resumed. In the esmolol group, there was no development of stable ventricular rhythm disturbances (ventricular fibrillation (VF) or ventricular tachycardia (VT)) on the first day of the disease, in contrast to the control group (n=4; 6.67%). The differences were significant (p=0.04). The incidence of hospital deaths was low (n=1 in the control group), with no significant difference between the study and control groups (0% vs 1.7%).Conclusion. The study results confirm the favorable safety profile of esmolol. Intravenous esmolol administration reduced the incidence of life-threatening arrhythmias without increasing the frequency of conduction disturbances, bradycardia, or AHF. In most cases, discontinuation of the infusion was sufficient to manage bradycardia in the esmolol group.

Yimeng Wang, Liabette Escamilla, Yinzhou Wang et al.

Therapeutic homework (i.e., tasks assigned by therapists for clients to complete between sessions) is essential for effective psychotherapy, yet therapists often interpret fragmented client logs, assessments, and reflections within limited preparation time. Our formative study with licensed therapists revealed three critical design requirements: support for interpreting unstructured client self-reports, customization aligned with clinical objectives, and seamless integration across multiple data sources. We then designed and developed TheraTrack, a customizable, therapist-facing tool that integrates multi-dimensional data and leverages large language models to generate traceable summaries and support natural-language queries, to streamline between-session homework tracking. Our pilot study with 14 therapists showed that TheraTrack reduced their cognitive load, enabled verification through direct navigation from AI summaries to original data entries, and was adapted differently for private analysis compared to in-session use, with dependence varying based on therapist experience and usage duration. We also discuss design implications for clinician-centered AI for mental health.

Mehrnoosh Sadat Shirvani, Jackie Crowley, Cher Peng et al.

As digital tools increasingly mediate mental health care, self-clone chatbots can offer a uniquely novel approach to intra-personal exploration and self-derived support. Trained to replicate users' conversational patterns, self-clones allow users to talk to themselves through their digital replicas. Despite the promises, these systems may carry risks around identity confusion, negative reinforcement, and blurred user agency. Through interviews with 16 mental health professionals and 6 general users, we aim to uncover tensions and design opportunities in this emerging space to guide responsible self-clone design. Our analysis produces a design framework organized around three priorities: (1) defining goals and grounding the approach in existing therapeutic models, (2) design dimensions including the self-clone persona and user-clone relationship dynamics, and (3) considerations for minimizing potential emotional and ethical harms. This framework contributes an interdisciplinary foundation for designing self-clone chatbots as AI-mediated self-interaction tools that are emotionally and ethically attuned in mental health contexts.

Fengyu Wang, Fengyu Wang, Sen Tong et al.

Traditional cancer treatment methods often encounter limitations, such as poor targeting, low bioavailability, and high systemic toxicity. These challenges have led researchers to explore alternative therapeutic strategies. Nickel nanoparticles (NiNPs), owing to their distinctive physicochemical properties and tunable biocompatibility, have attracted considerable attention in cancer therapy and drug delivery applications. These nanomaterials demonstrate excellent magnetic properties, photothermal conversion capabilities, catalytic activity, and potential for multifunctionality and targeted drug delivery via surface modification. This review highlights recent advancements in the use of NiNPs for cancer treatment, emphasizing their advantages as drug carriers that enhance the bioavailability, targeting, and therapeutic efficacy of anticancer agents. Additionally, the synergistic applications of NiNPs in multimodal therapies, including magnetic hyperthermia, photothermal therapy, and chemodynamic therapy, are discussed, as well as their potential as theranostic platforms. Although nickel-based nanodelivery systems show significant promise for clinical translation, issues related to biosafety, degradation metabolism, and long-term toxicity remain and require further investigation to support their clinical application.

Sundas Khalid, Rafay Naseer, Aqsa Zaheen et al.

The present study focuses on developing novel gradient thin films for surface-based magnetic resonance imaging of fluids such as water. Four types of magnetic-polymer colloids were investigated as T2 contrast agents, including Janus magnetic-polystyrene and core–shell magnetic-poly(styrene/divinylbenzene/methacrylic acid) particles. These colloids were coated with amino dextran to enhance their performance. Key factors such as emulsion composition, particle size, and surface properties were systematically examined. Gradient thin films were fabricated on glass slides using a layer-by-layer self-assembled multilayer (LbL-SAMu) technique. The films consisted of positively charged poly(dimethyl diallyl ammonium chloride) and negatively charged magnetic-polymer colloids. The developed colloids and thin films were characterized by their surface wettability, surface morphology, and zeta potential. These films exhibited relatively improved hydrophilicity and T2 contrast. The utilization of such gradient thin films as molecular probes could enhance clinical MRI for in vitro diagnosis. This study indicated that thin-film gradients can offer a facile technique for unique cellular imaging via a lab-on-chip device to enable effective point-of-care molecular diagnostics.

Constantina-Bianca Vulpe, Adina-Daniela Iachimov-Datcu, Andrijana Pujicic et al.

Triazole fungicides are widely used in agriculture but may pose risks to human health through occupational, accidental, or environmental exposure. This systematic review aimed to evaluate the toxicity of ten European Union-approved triazole fungicides in rodent models and cell lines. A total of 70 studies were included, reporting quantitative in vivo oral, dermal, or inhalation toxicity in mammals or quantitative in vitro cytotoxicity in human or mammalian cell lines; the exclusion criteria comprised publications not in English or not accessible. Literature searches were conducted in Web of Science, Google Scholar, and the Pesticide Properties DataBase (PPDB), and risk of bias in included studies was assessed using ToxRTool. Due to heterogeneity in study designs, reporting formats, and endpoints, data were synthesized descriptively. Quantitative endpoints included LD₅₀/LC₅₀ values for in vivo studies and LOEC, IC₅₀, LC₅₀, and EC₅₀ values for in vitro studies, while mechanistic endpoints highlighted apoptosis, oxidative stress, genotoxicity, and endoplasmic reticulum stress. Difenoconazole and tebuconazole were the most extensively studied compounds, whereas several triazoles had limited data. The limitations included heterogeneity of data and incomplete reporting, which restrict cross-study comparisons. Overall, the findings provide a comprehensive overview of potential human health hazards associated with EU-approved triazole fungicides and highlight critical knowledge gaps. The review was registered in Open Science Framework.

Xinxin Yu, Yimeng Wang, Long Chen et al.

Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures. Nonetheless, they also form a major source of prediction error in structure-activity relationship (SAR) models. To date, several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs. In this paper, we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet, tailored for ACs. Through extensive comparison with multiple baseline models on 30 benchmark datasets, the results showed that ACtriplet was significantly better than those deep learning (DL) models without pre-training. In addition, we explored the effect of pre-training on data representation. Finally, the case study demonstrated that our model's interpretability module could explain the prediction results reasonably. In the dilemma that the amount of data could not be increased rapidly, this innovative framework would better make use of the existing data, which would propel the potential of DL in the early stage of drug discovery and optimization.

Liying Wang, Ph. D., Daffodil Carrington et al.

Family caregivers often face substantial mental health challenges due to their multifaceted roles and limited resources. This study explored the potential of a large language model (LLM)-powered conversational agent to deliver evidence-based mental health support for caregivers, specifically Problem-Solving Therapy (PST) integrated with Motivational Interviewing (MI) and Behavioral Chain Analysis (BCA). A within-subject experiment was conducted with 28 caregivers interacting with four LLM configurations to evaluate empathy and therapeutic alliance. The best-performing models incorporated Few-Shot and Retrieval-Augmented Generation (RAG) prompting techniques, alongside clinician-curated examples. The models showed improved contextual understanding and personalized support, as reflected by qualitative responses and quantitative ratings on perceived empathy and therapeutic alliances. Participants valued the model's ability to validate emotions, explore unexpressed feelings, and provide actionable strategies. However, balancing thorough assessment with efficient advice delivery remains a challenge. This work highlights the potential of LLMs in delivering empathetic and tailored support for family caregivers.

Youngjae Yoo, Minuk Kim, Soyoung Kim et al.

Background: Despite the clinical effectiveness of digital interventions for young adults with depression, low engagement and adherence remain persistent challenges. Building a strong digital therapeutic alliance has been proposed to address these barriers. This study highlights the need for a conversational therapeutic companion agent (TCA)-based intervention design. Objective: This study aimed to develop a Wizard-of-Oz TCA-centered prototype integrating social-support-based ecological momentary assessment (EMA), ecological momentary intervention (EMI), behavioral activation, and gamification. We evaluated the six-week proof-of-concept efficacy of this intervention among young adults with depressive symptoms. Methods: Korean young adults aged 20--39 years with mild-to-moderate depressive symptoms (PHQ-9) were recruited online. The intervention group ($n = 29$) received a six-week TCA-based digital intervention, while the control group ($n = 29$), recruited four weeks later, continued their usual routines. The TCA guided four daily behavioral-activation tasks, three mood assessments, meditation, daily summaries, and weekly mission feedback. Both groups were assessed at baseline and at weeks 2, 4, and 6 using the BDI-II, GAD-7, and Q-LES-Q-SF. Results: Of 58 participants, 57 completed the study (one dropout in the intervention group). At week 6, the intervention group showed significantly greater reductions in depressive symptoms and improvements in quality of life than controls. Adherence was 78\% for EMA, 51\% for EMI, and 65\% for daily routines. Conclusions: The TCA-based digital intervention improved depressive symptoms and quality of life with adherence levels comparable to previous digital health interventions. Future studies should refine the TCA design and conduct larger-scale evaluations.

Soraya S. Anvari, Rina R. Wehbe

Large Language Models (LLMs) are increasingly deployed in mental health contexts, from structured therapeutic support tools to informal chat-based well-being assistants. While these systems increase accessibility, scalability, and personalization, their integration into mental health care brings privacy and safety challenges that have not been well-examined. Unlike traditional clinical interactions, LLM-mediated therapy often lacks a clear structure for what information is collected, how it is processed, and how it is stored or reused. Users without clinical guidance may over-disclose personal information, which is sometimes irrelevant to their presenting concern, due to misplaced trust, lack of awareness of data risks, or the conversational design of the system. This overexposure raises privacy concerns and also increases the potential for LLM bias, misinterpretation, and long-term data misuse. We propose a framework embedding Artificial Intelligence (AI) literacy interventions directly into mental health conversational systems, and outline a study plan to evaluate their impact on disclosure safety, trust, and user experience.

Occupational Therapy International

Rahul Nachnani, Amy Knehans, Jeffrey D. Neighbors et al.

BackgroundThe recent exponential increase in legalized medical and recreational cannabis, development of medical cannabis programs, and production of unregulated over-the-counter products (e.g., cannabidiol (CBD) oil, and delta-8-tetrahydrocannabinol (delta-8-THC)), has the potential to create unintended health consequences. The major cannabinoids (delta-9-tetrahydrocannabinol and cannabidiol) are metabolized by the same cytochrome P450 (CYP) enzymes that metabolize most prescription medications and xenobiotics (CYP3A4, CYP2C9, CYP2C19). As a result, we predict that there will be instances of drug-drug interactions and the potential for adverse outcomes, especially for prescription medications with a narrow therapeutic index.MethodsWe conducted a systematic review of all years to 2023 to identify real world reports of documented cannabinoid interactions with prescription medications. We limited our search to a set list of medications with predicted narrow therapeutic indices that may produce unintended adverse drug reactions (ADRs). Our team screened 4,600 reports and selected 151 full-text articles to assess for inclusion and exclusion criteria.ResultsOur investigation revealed 31 reports for which cannabinoids altered pharmacokinetics and/or produced adverse events. These reports involved 16 different Narrow Therapeutic Index (NTI) medications, under six drug classes, 889 individual subjects and 603 cannabis/cannabinoid users. Interactions between cannabis/cannabinoids and warfarin, valproate, tacrolimus, and sirolimus were the most widely reported and may pose the greatest risk to patients. Common ADRs included bleeding risk, altered mental status, difficulty inducing anesthesia, and gastrointestinal distress. Additionally, we identified 18 instances (58%) in which clinicians uncovered an unexpected serum level of the prescribed drug. The quality of pharmacokinetic evidence for each report was assessed using an internally developed ten-point scale.ConclusionDrug-drug interactions with cannabinoids are likely amongst prescription medications that use common CYP450 systems. Our findings highlight the need for healthcare providers and patients/care-givers to openly communicate about cannabis/cannabinoid use to prevent unintended adverse events. To that end, we have developed a free online tool (www.CANN-DIR.psu.edu) to help identify potential cannabinoid drug-drug interactions with prescription medications.

Dong Ha Kim, Hyojeong Park, Yun Jung Choi et al.

Abstract Background Small cell lung cancer (SCLC) has an exceptionally poor prognosis; as most of the cases are initially diagnosed as extensive disease with hematogenous metastasis. Therefore, the early diagnosis of SCLC is very important and may improve its prognosis. Methods To investigate the feasibility of early diagnosis of SCLC, we examined exosomal microRNAs (miRNAs) present in serum obtained from patients with SCLC. First, exosomes were isolated in serum from patients with SCLC and healthy individuals and were characterized using particle size and protein markers. Additionally, miRNA array was performed to define SCLC-specific exosomal miRNAs. Second, the obtained miRNAs were further validated employing a large cohort. Finally, the ability to diagnose SCLC was estimated by area under the curve (AUC), and intracellular mRNA change patterns were verified through validated miRNAs. Results From the miRNA array results, we selected 51-miRNAs based on p-values and top 10 differentially expressed genes, and 25-miRNAs were validated using quantitative reverse transcription-polymerase chain reaction. The 25-miRNAs were further validated employing a large cohort. Among them, 7-miRNAs showed significant differences. Furthermore, 6-miRNAs (miR-3565, miR-3124-5p, miR-200b-3p, miR-6515, miR-3126-3p and miR-9-5p) were up-regulated and 1-miRNA (miR-92b-5p) was down-regulated. The AUC value of each miRNA sets between 0.64 and 0.76, however the combined application of 3-miRNAs (miR-200b-3p, miR-3124-5p and miR-92b-5p) remarkably improved the diagnostic value (AUC = 0.93). Gene ontology analysis revealed that the 3-miRNA panel is linked to various oncogene pathways and nervous system development. When the 3-miRNAs were introduced to cells, the resulting changes in total mRNA expression strongly indicated the presence of lung diseases, including lung cancer. In addition, the 3-miRNA panel was significantly associated with a poorer prognosis, although individual miRNAs have not been validated as prognostic markers. Conclusion Our study identified SCLC-specific exosomal miRNAs, and the 3-miRNAs panel (miR-200b-3p, miR-3124-5p and miR-92b-5p) may serve as a diagnostic and prognostic marker for SCLC. Graphical abstract

Zhou W, Hu S, Wu Y et al.

Wenyu Zhou,1,* Song Hu,1,2,* Yutong Wu,1,* Huan Xu,1,* Lina Zhu,1 Huimin Deng,1 Sheng Wang,1 Yuanli Chen,1 Huanping Zhou,1 Xin Lv,1 Quanfu Li,1 Hao Yang1 1Department of Anesthesiology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, People’s Republic of China; 2Graduate School, Wannan Medical College, Wuhu, AnHui, 241002, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hao Yang, Department of Anesthesiology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, 507 Zhengmin Road, Shanghai, 200433, People’s Republic of China, Email yanghaozunyi@sina.com Quanfu Li, Department of Anesthesiology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zhengmin Road, Shanghai, 200433, People’s Republic of China, Email quanfuli185@163.comBackground: Mesenchymal stem cell-derived exosomes (MSC-exosomes) have been found to effectively improve the systemic inflammatory response caused by acute lung injury and acute respiratory distress syndrome (ALI/ARDS), regulate systemic immune disorders, and help injured cells repair. The purpose of this study was to take a holistic view of the current status and trends of MSC-exosomes research in ALI/ARDS.Methods: Bibliometrix, Citespace and VOSviewer software were used for bibliometric analysis of the data. We analysed the world trends, country distribution, institution contribution, most relevant journals and authors, research hotspots, and research hotspots related to Coronavirus Disease 2019 (COVID-19) based on the data collected.Results: China possessed the largest number of publications, while the USA had the highest H-index and the number of citations. Both China and the USA had a high influence in this research field. The largest number of publications in the field of MSC-exosomes and ALI/ARDS were mainly from the University of California system. Stem Cell Research & Therapy published the largest number of papers in this scope. The author with the greatest contribution was LEE JW, and ZHU YG published an article in Stem Cell with the highest local citation score. The most frequent keyword and the latest research hotspot were “NF-κB” and “Coronavirus Disease 2019”. Furthermore, our bibliometric analysis results demonstrated that MSC-exosomes intervention and treatment can effectively alleviate the inflammatory response caused by ALI/ARDS.Conclusion: Our bibliometric study suggested the USA and China have a strong influence in this field. COVID-19-induced ALI/ARDS had become a hot topic of research.Keywords: acute respiratory distress syndrome, mesenchymal stem cells, exosome, bibliometrix, Citespace, VOSviewer

Yury E. Geints, Ekaterina K. Panina

Multilayer microparticles with a liquid core and a polycomposite light-absorbing shell are important components of modern bio- and medical technologies, in particular, as transport microcontainers in the system of targeted delivery of therapeutic nanodoses to the desired region of the biological tissues. For reliably opening the microcapsule shell by an optical radiation and releasing the payload, it is necessary to dramatically increase the light absorption of such a microcontainer. To this end, we propose surrounding the microcapsule with specially added auxiliary nanoparticles, which can accumulate optical energy near its surface and direct a concentrated photonic flux to the target microcapsule thus leading to its booster heating. Using numerical finite-difference time-domain (FDTD) calculations, we simulate and examine the absorption dynamics of the near-infrared optical radiation in a spherical microcapsule surrounded by solid nanoparticles of different optical properties (metal, biocompatible dielectric). We show that due to light scattering on nanoparticles, the optical field superlocalization in the "hot regions" on the microcapsule surface occurs. The three-fold light absorption enhancement can be achieved due to the addition of nanoparticles.

Hans Rabus, Miriam Schwarze, Leo Thomas

In the recently published article by T.M. Gray et al. "Microdosimetric and radiobiological effects of gold nanoparticles at therapeutic radiation energies" (IJRB 2023, 99(2), 308-317) results of Monte Carlo simulations and radiobiological assays on the dosimetric effects of gold nanoparticles were presented. This commentary points out that the results of the two parts of the study are in contradiction and that the predicted magnitude of dose enhancement and its dependence on the shape of the nanoparticle appear implausible. Possible reasons for these observations are discussed.

Oncay Yasa, Fikru M. Tiruneh, Miriam Filippi et al.

Hydrogels engineered for medical use within the human body need to be delivered in a minimally invasive fashion without altering their biochemical and mechanical properties to maximize their therapeutic outcomes. In this regard, key strategies applied for creating such medical hydrogels include formulating precursor solutions that can be crosslinked in situ with physical or chemical cues following their delivery or forming macroporous hydrogels at sub-zero temperatures via cryogelation prior to their delivery. Here, we present a new class of injectable composite materials with shape recovery ability. The shape recovery is derived from the physical properties of red blood cells (RBCs) that are first modified via hypotonic swelling and then integrated into the hydrogel scaffolds before polymerization. The RBCs' hypotonic swelling induces the formation of nanometer-sized pores on their cell membranes, which enable fast liquid release under compression. The resulting biocomposite hydrogel scaffolds display high deformability and shape-recovery ability. The scaffolds can repeatedly compress up to ~87% of their original volumes during injection and subsequent retraction through syringe needles of different sizes; this cycle of injection and retraction can be repeated up to ten times without causing any substantial mechanical damage to the scaffolds. Our biocomposite material system and fabrication approach for injectable materials will be foundational for the minimally invasive delivery of drug-loaded scaffolds, tissue-engineered constructs, and personalized medical platforms that could be administered to the human body with conventional needle-syringe systems.

Srivastava RK, Sapra L

Rupesh K Srivastava, Leena Sapra Immunoporosis Lab, Department of Biotechnology, All India Institute of Medical Sciences (AIIMS), New Delhi, 110029, IndiaCorrespondence: Rupesh K Srivastava, Tel +91 11-26593548, Email rupesh_srivastava13@yahoo.co.in; rupeshk@aiims.eduAbstract: Discoveries in the last few years have emphasized the existence of an enormous breadth of communication between bone and the immune system in maintaining skeletal homeostasis. Originally, the discovery of various factors was assigned to the immune system viz. interleukin (IL)-6, IL-10, IL-17, tumor necrosis factor (TNF)-α, receptor activator of nuclear factor kappa B ligand (RANKL), nuclear factor of activated T cells (NFATc1), etc., but now these factors have also been shown to have a significant impact on osteoblasts (OBs) and osteoclasts (OCs) biology. These discoveries led to an alteration in the approach for the treatment of several bone pathologies including osteoporosis. Osteoporosis is an inflammatory bone anomaly affecting more than 500 million people globally. In 2018, to highlight the importance of the immune system in the pathophysiology of osteoporosis, our group coined the term “immunoporosis”. In the present review, we exhaustively revisit the characteristics, mechanism of action, and function of both innate and adaptive immune cells with the goal of understanding the potential of immune cells in osteoporosis. We also highlight the Immunoporotic role of gut microbiota (GM) for the treatment and management of osteoporosis. Importantly, we further discuss whether an immune cell-based strategy to treat and manage osteoporosis is feasible and relevant in clinical settings.Graphical Abstract: Keywords: immunoporosis, innate immune cells, adaptive immune cells, bone cells, gut microbiota, osteoporosis

Shanjukta Nath, Keith Warren, Subhadeep Paul

We investigate peer role model influence on successful graduation from Therapeutic Communities (TCs) for substance abuse and criminal behavior. We use data from 3 TCs that kept records of exchanges of affirmations among residents and their precise entry and exit dates, allowing us to form peer networks and define a causal effect of interest. The role model effect measures the difference in the expected outcome of a resident (ego) who can observe one of their peers graduate before the ego's exit vs not graduating. To identify peer influence in the presence of unobserved homophily in observational data, we model the network with a latent variable model. We show that our peer influence estimator is asymptotically unbiased when the unobserved latent positions are estimated from the observed network. We additionally propose a measurement error bias correction method to further reduce bias due to estimating latent positions. Our simulations show the proposed latent homophily adjustment and bias correction perform well in finite samples. We also extend the methodology to the case of binary response with a probit model. Our results indicate a positive effect of peers' graduation on residents' graduation and that it differs based on gender, race, and the definition of the role model effect. A counterfactual exercise quantifies the potential benefits of an intervention directly on the treated resident and indirectly on their peers through network propagation.

Fereshteh Shahmiri, Steven Schwartz, Can Usanmaz

This work presents a triboelectric nanogenerator-based (TENG) therapeutic stress ball to provide gesture monitoring and physiological data on patients requiring physical therapy of various degrees. The device utilizes a 5-layer stack of silicone and braided silver-coated nylon rope electrodes to create a sensor network that monitors 40-points across the surface of a semi-spherical prototype. A modified version of a standard ECG circuit was utilized to provide proper loading, noise rejection, filtering, and phase of the TENG signals along with multiplexing of the many electrodes. All system components were selected with a final embedded system in mind. Testing of the device was conducted utilizing an Arduino Uno and an EVAL-AD5940BIOZ evaluation board for electrodermal activity for stress and/or pain after exercise. An accelerometer was included for device activation and hand tremor detection. Upon testing, the self-powered TENG sensors produce positive impulses upon contact and negative impulses upon release of contact from the surface of the ball. Furthermore, finger removal detection was demonstrated by capturing the associated negative impulse by maintaining the bipolar signal in our conditioning circuit. EDA results indicate silver-coated nylon as a potentially good dry-electrode which can be used with even more electrodes for bio-impedance or ECG capture to further expand the device functionality. A MATLAB-based GUI was designed to provide the user with data tracking and visual monitoring of the data via serial communication from the microcontrollers. Finally, it should be noted that this provides a means for low-cost low-power gesture tracking without the use of flexible capacitive grid arrays and provides the user with a pleasant tactile experience that one expects form a stress ball due to its unique material design.