A5075232886- Parkinson's Disease Mechanisms and Treatments
- Balance, Gait, and Falls Prevention
- Emotion and Mood Recognition
- Muscle activation and electromyography studies
- Stroke Rehabilitation and Recovery
- Context-Aware Activity Recognition Systems
- Neurological disorders and treatments
- Indoor and Outdoor Localization Technologies
- Voice and Speech Disorders
- Assistive Technology in Communication and Mobility
- Autism Spectrum Disorder Research
- Gait Recognition and Analysis
- Cerebral Palsy and Movement Disorders
- Diabetic Foot Ulcer Assessment and Management
- Non-Invasive Vital Sign Monitoring
- Wireless Body Area Networks
- Cardiac Health and Mental Health
- Energy Efficient Wireless Sensor Networks
- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
- Hip and Femur Fractures
- Color perception and design
- E-commerce and Technology Innovations
- Biomedical and Engineering Education
- Ergonomics and Musculoskeletal Disorders
Marche Polytechnic University
2016-2025
In this work we propose a real-time detection of mental stress during different cognitive tasks. Stress is classified processing Galvanic Skin Response (GSR), RR Interval and Body Temperature (BT) acquired by commercial smartwatch. The unobtrusive system proposed validated through clinical psychological tests.
The freezing of gait (FOG) is a common and highly distressing motor symptom patients with Parkinson's Disease (PD). Effective management FOG difficult given its episodic nature, heterogeneous manifestation limited responsiveness to drug treatment. Clinicians found alternative approaches, such as rhythmic cueing. We built smartphone-based architecture in agreement acceptability usability requirements which able gather data information useful detect FOG. In this work fusing together the freeze...
The problem of continuous emotion recognition has been the subject several studies. proposed affective computing approaches employ sequential machine learning algorithms for improving classification stage, accounting time ambiguity emotional responses. Modeling and predicting state over is not a trivial because data labeling costly always feasible. This crucial issue in real-life applications, where sparse possibly captures only most important events rather than typical subtle changes that...
Detecting stress in computer users, while technically challenging, is of the utmost importance workplace, especially now that remote working scenarios are becoming ubiquitous. In this context, cost-effective, subject-independent systems needed can be embedded consumer devices and classify users' a reliable unobtrusive fashion. Leveraging keyboard mouse dynamics particularly appealing context as it exploits readily available sensors. However, studies mostly performed laboratory conditions,...
Objectives: Having achieved a consolidated in-hospital experience with enhanced recovery after cardiac surgery, we explored the feasibility of expanding our protocol to pre-admission and post-discharge periods. Methods: A multidisciplinary team including surgeons, anaesthetists/intensivists, physiatrists, physiotherapists, perfusionists, nurses, psychiatrists, engineers, elaborated new therapeutic offer, based on current ERAS evidence using telerehabilitation, enhance preoperative...
Telemedicine systems for remote monitoring are gaining importance given the increase in aging population. Possible limitations to their diffusion daily living situations can lay on usability and social acceptability barriers. In this work we propose an architecture management of motor disorders applied Parkinsonian patients suffering Freezing Gait (FoG). The is composed a smartphone app, database (DB) web hence it uses only technologies that well known diffuse among society. app monitors...
We built a smartphone-based architecture to detect on line Freezing of Gait (FOG) occurrences and send acoustic signals restore gait. Parameters used for FOG detection events are stored in local database periodically sent clinical server. tested this solution 18 patients.
Health monitoring is nowadays one of the hottest markets due to increasing interest in prevention and treatment physical problems. In this context development wearable, wireless, open-source, nonintrusive sensing solutions still an open problem. Indeed, most existing commercial architectures are closed provide little flexibility. paper, hardware architecture for designing a modular wireless sensor node health proposed. By separating connection functions two separate boards, compliant with...
Step Length (SL) is an essential parameter in the healthcare field to monitor gait of patients affected by motor disorders such as Freezing Gait (FoG), a block that provokes interruption normal cycle. As consequence spatio-temporal parameters gait, particular SL, are strongly altered before and during FoG event. In this work we present non-intrusive non-invasive architecture applicable clinical scenario evaluate its reliability SL estimation on 8 healthy subjects. We obtained mean errors...
Smartphones are particularly suitable for health related applications during daily living, given their diffusion into society and computational capabilities. We proposed a smartphone application real-time step length estimation, using inverted pendulum model. tested the solution on 5 healthy subjects, comparing estimation with stereophotogrammetric system.