Revolutionizing the construction industry by cutting edge artificial intelligence approaches: a review.

The construction industry is rapidly adopting Industry 4.0 technologies, creating new opportunities to address persistent environmental and operational challenges. This review focuses on how Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are being leveraged to tackle these issues.

[Clinical Thermography for the Management of Hemodialysis Vascular Access].

The arteriovenous fistula (AVF) represents the favorite vascular access in individuals with chronic kidney disease (CKD). Because AVF is a guarantee of survival for these patients, proper surgical packing and a timely follow-up program is crucial. Although a good objective examination of the limb site of FAV provides useful information both in planning the fistula surgery and in its surveillance and monitoring, it is now well established that the advent of instrumental diagnostics (ultrasonography, digital angiography, Angio-TC, MRI) has contributed significantly to improving primary and secondary patency of FAV and early diagnosis of vascular access complications.

Integrating Machine Learning with Robotic Rehabilitation May Support Prediction of Recovery of the Upper Limb Motor Function in Stroke Survivors.

Motor impairment is a common issue in stroke patients, often affecting the upper limbs. To this standpoint, robotic neurorehabilitation has shown to be highly effective for motor function recovery. Notably, Machine learning (ML) may be a powerful technique able to identify the optimal kind and intensity of rehabilitation treatments to maximize the outcomes.

Predicting Sleep Quality through Biofeedback: A Machine Learning Approach Using Heart Rate Variability and Skin Temperature.

Sleep quality (SQ) is a crucial aspect of overall health. Poor sleep quality may cause cognitive impairment, mood disturbances, and an increased risk of chronic diseases. Therefore, assessing sleep quality helps identify individuals at risk and develop effective interventions.

Data-Driven Identification of Stroke through Machine Learning Applied to Complexity Metrics in Multimodal Electromyography and Kinematics.

A stroke represents a significant medical condition characterized by the sudden interruption of blood flow to the brain, leading to cellular damage or death. The impact of stroke on individuals can vary from mild impairments to severe disability. Treatment for stroke often focuses on gait rehabilitation.

Female patients have greater improvement in pain symptoms and physical activity after fasciotomy for treatment of chronic exertional compartment syndrome of the lower leg.

Purpose: The purpose of this study was to identify sex differences in postoperative outcomes and return-to-sport rates after fasciotomy for treatment of chronic exertional compartment syndrome (CECS) of the lower leg. It was hypothesised that male CECS patients would have a higher rate of return to sport than female CECS patients.

Methods: A retrospective cohort study was conducted involving patients who underwent primary fasciotomy of one to four leg compartments for treatment of CECS at a single centre from 2010 to 2020.

Emerging effects of temperature on human cognition, affect, and behaviour.

Human body core temperature is tightly regulated within approximately 37 °C. Global near surface temperature has increased by over 1.2 °C between 1850 and 2020.

Local effect of allopregnanolone in rat ovarian steroidogenesis, follicular and corpora lutea development.

Allopregnanolone (ALLO) is a known neurosteroid and a progesterone metabolite synthesized in the ovary, CNS, PNS, adrenals and placenta. Its role in the neuroendocrine control of ovarian physiology has been studied, but its in situ ovarian effects are still largely unknown. The aims of this work were to characterize the effects of intrabursal ALLO administration on different ovarian parameters, and the probable mechanism of action.

Assessing the Impact of Electrosuit Therapy on Cerebral Palsy: A Study on the Users' Satisfaction and Potential Efficacy.

The aim of this study is to evaluate the effectiveness of electrosuit therapy in the clinical treatment of children with Cerebral Palsy, focusing on the effect of the therapy on spasticity and trunk control. Moreover, the compliance of caregivers with respect to the use of the tool was investigated. During the period ranging from 2019 to 2022, a total of 26 children (18 M and 8 F), clinically stable and affected by CP and attending the Neurorehabilitation Unit of the "Padre Pio Foundation and Rehabilitation Centers", were enrolled in this study.

Assessing Feasibility of Cognitive Impairment Testing Using Social Robotic Technology Augmented with Affective Computing and Emotional State Detection Systems.

Social robots represent a valid opportunity to manage the diagnosis, treatment, care, and support of older people with dementia. The aim of this study is to validate the Mini-Mental State Examination (MMSE) test administered by the Pepper robot equipped with systems to detect psychophysical and emotional states in older patients. Our main result is that the Pepper robot is capable of administering the MMSE and that cognitive status is not a determinant in the effective use of a social robot.

Facial functional networks during resting state revealed by thermal infrared imaging.

In recent decades, an increasing number of studies on psychophysiology and, in general, on clinical medicine has employed the technique of facial thermal infrared imaging (IRI), which allows to obtain information about the emotional and physical states of the subjects in a completely non-invasive and contactless fashion. Several regions of interest (ROIs) have been reported in literature as salient areas for the psychophysiological characterization of a subject (i.e.

Clinical Presentation and Outcomes of Sacral Stress Fractures in Athletes: A Case Series of 13 Patients.

Background: Sacral stress fractures are a rare cause of low back pain in athletes. Given the low incidence of these fractures, there is a scarcity of data on symptomatology, risk factors, and clinical outcomes.

Hypothesis: Patients diagnosed with sacral stress fractures would be athletes presenting with low back pain.

Use and Effectiveness of Electrosuit in Neurological Disorders: A Systematic Review with Clinical Implications.

Electrical stimulation through surface electrodes is a non-invasive therapeutic technique used to improve voluntary motor control and reduce pain and spasticity in patients with central nervous system injuries. The Exopulse Mollii Suit (EMS) is a non-invasive full-body suit with integrated electrodes designed for self-administered electrical stimulation to reduce spasticity and promote flexibility. The EMS has been evaluated in several clinical trials with positive findings, indicating its potential in rehabilitation.

Effect of peripheral neural stimulation with allopregnanolone on ovarian physiology.

Neuroactive steroids can rapidly regulate multiple physiological functions in the central and peripheral nervous systems. The aims of the present study were to determine whether allopregnanolone (ALLO), administered in low nanomolar and high micromolar concentrations, can: (i) induce changes in the ovarian progesterone (P4) and estradiol (E2) release; (ii) modify the ovarian mRNA expression of Hsd3b1 (3β-hydroxysteroid dehydrogenase, 3β-HSD)3β-, Akr1c3 (20α-hydroxysteroid dehydrogenase, 20α-HSD), and Akr1c14 (3α-hydroxy steroid oxidoreductase, 3α-HSOR)); and (iii) modulate the ovarian expression of progesterone receptors A and B, α and β estrogenic receptors, luteinizing hormone receptor (LHR) and follicle-stimulating hormone receptor (FSHR). To further characterize ALLO peripheral actions, the effects were evaluated using a superior mesenteric ganglion-ovarian nervous plexus-ovary (SMG-ONP-O) and a denervated ovary (DO) systems.

Psychiatric Disorders Are Predictive of Worse Pain Severity and Functional Outcomes After Fasciotomy for Chronic Exertional Compartment Syndrome of the Leg.

Objective: To determine whether concomitant psychiatric diagnoses and medication use were associated with postfasciotomy outcomes in patients with chronic exertional compartment syndrome (CECS).

Design: Retrospective comparative cohort study.

Setting: Single academic medical center from 2010 to 2020.

Intraoperative thermal infrared imaging in neurosurgery: machine learning approaches for advanced segmentation of tumors.

Surgical resection is one of the most relevant practices in neurosurgery. Finding the correct surgical extent of the tumor is a key question and so far several techniques have been employed to assist the neurosurgeon in preserving the maximum amount of healthy tissue. Some of these methods are invasive for patients, not always allowing high precision in the detection of the tumor area.

Can Data-Driven Supervised Machine Learning Approaches Applied to Infrared Thermal Imaging Data Estimate Muscular Activity and Fatigue?

Surface electromyography (sEMG) is the acquisition, from the skin, of the electrical signal produced by muscle activation. Usually, sEMG is measured through electrodes with electrolytic gel, which often causes skin irritation. Capacitive contactless electrodes have been developed to overcome this limitation.

Identification of Functional Cortical Plasticity in Children with Cerebral Palsy Associated to Robotic-Assisted Gait Training: An fNIRS Study.

Cerebral palsy (CP) is a non-progressive neurologic condition that causes gait limitations, spasticity, and impaired balance and coordination. Robotic-assisted gait training (RAGT) has become a common rehabilitation tool employed to improve the gait pattern of people with neurological impairments. However, few studies have demonstrated the effectiveness of RAGT in children with CP and its neurological effects through portable neuroimaging techniques, such as functional near-infrared spectroscopy (fNIRS).

Psychophysiological Assessment of Children with Cerebral Palsy during Robotic-Assisted Gait Training through Infrared Imaging.

Cerebral palsy (CP) is a non-progressive neurologic pathology representing a leading cause of spasticity and concerning gait impairments in children. Robotic-assisted gait training (RAGT) is widely employed to treat this pathology to improve children's gait pattern. Importantly, the effectiveness of the therapy is strictly related to the engagement of the patient in the rehabilitation process, which depends on his/her psychophysiological state.

Altered Microcirculation in Alzheimer's Disease Assessed by Machine Learning Applied to Functional Thermal Imaging Data.

Alzheimer's disease (AD) is characterized by progressive memory failures accompanied by microcirculation alterations. Particularly, impaired endothelial microvascular responsiveness and altered flow motion patterns have been observed in AD patients. Of note, the endothelium influences the vascular tone and also the small superficial blood vessels, which can be evaluated through infrared thermography (IRT).

Classification of Drivers' Mental Workload Levels: Comparison of Machine Learning Methods Based on ECG and Infrared Thermal Signals.

Mental workload (MW) represents the amount of brain resources required to perform concurrent tasks. The evaluation of MW is of paramount importance for Advanced Driver-Assistance Systems, given its correlation with traffic accidents risk. In the present research, two cognitive tests (Digit Span Test-DST and Ray Auditory Verbal Learning Test-RAVLT) were administered to participants while driving in a simulated environment.