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Controle de escorregamento baseado em modelo neuromimético embarcado adaptativo

2026-07-29T06:23:46Z

Title: Controle de escorregamento baseado em modelo neuromimético embarcado adaptativo Abstract: The ability to dexterously manipulate objects is a fundamental human skill based on fast reflex loops and tactile feedback. In upper-limb amputees, the lack of sensory perception in commercial prostheses is one of the leading causes of user rejection and device abandonment, with clinical abandonment rates reaching up to 30%. Mimicking the motor grasp reflex in real time (latency below 100 ms) is a major challenge in rehabilitation robotics due to the high computational cost of conventional methods and constraints of wearable hardware. This thesis proposes and validates the hypothesis that an embedded, bio-inspired event-driven architecture based on neuromorphic coding and fed by a high-density piezoresistive tactile array can detect and suppress slip locally and autonomously within timeframes compatible with the human reflex arc. The developed system integrates a 4 × 4 taxel piezoresistive sensor array covered by a 2 mm layer of EcoFlex 00-30 silicone on the fingertips of a commercial robotic prosthesis (COVVI Hand) coupled to an industrial manipulator (DOBOT CR10A). Analog pressure readings are locally converted into action potentials (spikes) using the Izhikevich neuron model to emulate slowly adapting (SA-I) and fast-adapting (FA-I) mechanoreceptors. Active slip suppression is executed using a Monotonic Proportional-Integral (MPI) controller operating at 500 Hz. Under abrupt perturbation (Experiment A: 20 g step load), the average suppression time was 70 ± 22 ms (FA-I) and 80 ± 25 ms (SA-I). Under progressive perturbation (Experiment B: water flow at 50 ml/s), the reaction times were 82 ± 28 ms (FA-I) and 95 ± 34 ms (SA-I). The main finding of this work is the demonstration that local event-driven processing successfully circumvents the non-linearities and hysteresis of the silicone, enabling low-cost microcontrollers to run fast and robust closed-loop reflex controls. In conclusion, the proposed embedded neuromorphic architecture enables energy-efficient wearable solutions, which are essential for real functional upper-limb rehabilitation.

Efeitos dos Canabinoides no Tremor Parkinsoniano e interações medicamentosas: análise por inteligência artificial explicável dos dados Fox Insight

2026-06-04T06:19:20Z

Title: Efeitos dos Canabinoides no Tremor Parkinsoniano e interações medicamentosas: análise por inteligência artificial explicável dos dados Fox Insight Abstract: Parkinson’s disease constitutes the second most prevalent neurodegenerative condition worldwide, affecting 1-2% of the population over 65 years of age, with tremor present in 70% of cases. Conventional pharmacological treatments present limitations in 30-40% of patients, establishing the need for therapeutic alternatives. This thesis aimed to develop an explainable artificial intelligence methodology for personalizing medical cannabis use in treating parkinsonian tremor, quantifying determinants of individual heterogeneity in therapeutic response. The methodology employed analysis based on SHAP (SHapley Additive exPlanations) values applied to 2,616 records from the Fox Insight platform, structured in three progressive datasets: SINGLE (n=973, isolated cannabis), FULL_NUMERICO (n=931, pharmacological groups), and FULL_GFEM (n=931, detailed individual characteristics). Machine learning models achieved elevated performance metrics: SINGLE (LightGBM) with accuracy 96.31%, precision 96.33%, recall 96.31%, F1-score 96.31%, and specificity 96.03%; FULL_NUMERICO (LightGBM) with accuracy 97.42%, precision 97.47%, recall 97.42%, F1-score 97.42%, and specificity 97.07%; FULL_GFEM (XGBoost) with accuracy 97.42%, precision 97.54%, recall 97.42%, F1-score 97.42%, and specificity 96.91%, demonstrating that interpretability does not compromise predictive performance when architecture is adequately designed. Results quantified eight main findings: (1) pronounced sexual dimorphism, with women presenting mean SHAP values of +1.52 ± 0.48 (improvement rate 94.1%) versus men -0.93 ± 0.37 (rate 38.5%), establishing a magnitude of 2.44x in the probability of favorable response; (2) identification of six distinct profiles through clustering, with 55% of patients presenting elevated improvement rates (89% to 100%) and SHAP values between +1.94 and +2.57; (3) non-linear inverted-U age pattern, with critical group 60-70 years (n=559, 60% of sample) presenting worse response (rate 38.8%) and partial recovery in 70-80 years (rate 76.2%, n=181); (4) hierarchy of administration routes quantified by MASV (Mean Absolute SHAP Value): oil (0.705) > sublingual (0.4959) > food (0.657 Class 1), demonstrating importance superior to dose; (5) bifasic optimal therapeutic windows for THC (1.5-2.5 mg/day, MASV = 0.2888) and CBD (2-4 mg/day, MASV = 0.2654), empirically validating that supra-therapeutic doses reduce efficacy; (6) quantified synergy with MAO-B inhibitors (MASV = 0.4485), superior to interactions with levodopa (MASV = 0.2506) and other dopaminergics (MASV = 0.2454); (7) moderate optimal frequency of 3-5 times/week, superior to continuous daily use; (8) therapeutic learning curve with optimization in 2-3 years and possible tolerance after >3 years. Findings were operationalized in a clinical nomogram that stratifies patients into five predictive categories, with 87.3% concordance with phenotypic clusters. Computational analysis through clustering identified difference in improvement rates between subgroups with elevated response (89-100%, n=513) and general population (66.4%, n=931), suggesting potential for therapeutic personalization based on identifiable clinical characteristics, hypothesis requiring confirmation in future clinical studies. This investigation establishes a new methodological standard for research in precision neurological medicine, providing computational tools and quantitative knowledge for prospective identification of subgroups with high probability of benefit, individualized therapeutic regimen optimization, and establishment of expectations based on measurable patient characteristics.

Avaliação da atividade eletromiográfica de músculos do core no exercício prancha ventral até a exaustão com e sem exergame plankpad

2026-05-20T06:29:41Z

Title: Avaliação da atividade eletromiográfica de músculos do core no exercício prancha ventral até a exaustão com e sem exergame plankpad Abstract: Core training plays an important role in quality of life, especially in reducing the prevalence of low back pain. Recently, exergames such as Plankpad have been developed to improve adherence to physical training and rehabilitation programs focused on core muscle strengthening. However, no studies have analyzed electromyographic (EMG) activity during the ventral plank (VP) exercise with and without exergame, including time-domain and frequency-domain analysis as well as muscle co-contraction. This study aimed to investigate the effects of incorporating the Plankpad exergame on core muscle EMG activity during the VP exercise until exhaustion. Fifteen young, healthy, physically active men with no history of low back pain participated. Participants performed the VP exercise until exhaustion under five conditions: stable ground (VP-GR), Plankpad platform without game (VP-PP), and Plankpad platform with the Fruit Splicer game at easy (VP-EA), medium (VP-ME), and hard (VP-HA) levels. EMG signals were collected from the rectus abdominis (RA), external oblique (EO), internal oblique (IO), erector spinae (ES), and multifidus (MU) muscles, along with time to exhaustion and rating of perceived exertion (RPE). Results showed progressive increases in RMS and decreases in median frequency (MF) over time in all exercises, indicating peripheral neuromuscular fatigue, with no significant differences among the five conditions for most parameters. Local co-contraction (IO/MU) was significantly higher in VP-PP compared to VP EA and decreased with fatigue across all exercises. Time to exhaustion and RPE were similar among conditions. Correlations between RPE and EMG parameters were weak to moderate. We conclude that the Plankpad exergame, at easy, medium, and hard levels, does not increase electromyographic activation, spectral fatigue, time to exhaustion, or RPE compared to traditional plank exercise in young healthy trained men.

Avaliação dos protocolos de morte encefálica

2026-03-06T06:22:17Z

Title: Avaliação dos protocolos de morte encefálica Abstract: The inherent complexity and urgency of diagnosing Brain Death (BD) constitute a persistent challenge in Intensive Care Units (ICU), representing a critical factor for the success of the National Transplant Policy (PNT). BD, defined as the irreversible cessation of all brain functions, is the legal premise of death authorizing organ removal, in accordance with Law No. 9,434/97 and CFM Resolution No. 2,173/17. The ethical and logistical imperative demands absolute celerity and safety, given that delay compromises organ viability. Furthermore, initiating the BD diagnostic protocol entails a fatal prognosis, culminating either in BD confirmation or Cardiac Arrest (PCR). With the objective of optimizing the diagnosis and the rational use of ancillary tests, such as the Electroencephalogram (EEG), this thesis sought to establish a robust predictive score capable of differentiating progression to BD from Death by Cardiac Arrest (PCR) in neurocritical patients. The study was conducted as a retrospective cohort analysis, approved by the Ethics Committee (CEP) of the Universidade Federal de Uberlândia (UFU), utilizing an Analytical Sample of N=66 patients and applying Binary Logistic Regression to identify independent predictive factors. The statistical model confirmed that the outcome is primarily determined by the initial neurovascular severity. Two clinical factors were identified as the most robust predictors for the outcome of Brain Death: the initial Glasgow Coma Scale (GCS) score and the Use of Vasoactive Drugs (DVA). The initial GCS score proved to be the strongest independent predictor (OR = 1.70; p=0.002), indicating that the BD outcome is intrinsically linked to catastrophic initial neurological injury. Complementarily, the use of DVA was a strong predictor of BD (OR = 0.04; p=0.031), as the need for pressure support (observed in approximately 95% of BD cases) is a robust marker of neurogenic shock and brainstem failure, reducing the chance of death by PCR by 96%. Univariate analyses corroborated that Traumatic Brain Injury (TBI) etiology was significantly more prevalent in the BD Group (approximately 44% vs. 0% in the PCR Group; p=0.022), reinforcing the epidemiological profile of high-impact acute lesions. Furthermore, the extremely low rate of Cardiac Arrest in the BD Group (approximately 1.7%; p<0.001) attested to the high quality of intensive clinical management, maintaining organ viability until the legal declaration of death. Regarding ancillary testing, Quantitative EEG (QEEG) analysis in selected cases demonstrated that progression to BD is marked by a profound electrophysiological disorganization, featuring an inversion in power patterns and extreme, dysregulated variability of electrical activity. This reinforces the potential of EEG, due to its non-invasive and cost-effective nature, as an ideal tool within the reality of the public health system (SUS). The main practical contribution of this thesis resides in the proposition of the Predictive Triage Model (GCS + DVA). This model allows for the quicker and more focused activation of the BD protocol and complementary examinations, particularly concentrating on EEG use. This optimization directly contributes to maintaining organ viability. In summary, the work demonstrates that the integration of methodological rigor from data science with clinical physiology establishes powerful tools to refine the diagnosis of Brain Death, ensuring the excellence and efficiency demanded by the ethical and legal imperative