Stefano Bertuletti
A5072043053- Balance, Gait, and Falls Prevention
- Gait Recognition and Analysis
- Cerebral Palsy and Movement Disorders
- Diabetic Foot Ulcer Assessment and Management
- Context-Aware Activity Recognition Systems
- Anomaly Detection Techniques and Applications
- Stroke Rehabilitation and Recovery
- Indoor and Outdoor Localization Technologies
- Non-Invasive Vital Sign Monitoring
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Prosthetics and Rehabilitation Robotics
- Muscle activation and electromyography studies
- Human Mobility and Location-Based Analysis
- Medical Imaging Techniques and Applications
- Lower Extremity Biomechanics and Pathologies
- Optical Imaging and Spectroscopy Techniques
- Telemedicine and Telehealth Implementation
- Injury Epidemiology and Prevention
- Flow Measurement and Analysis
- Video Surveillance and Tracking Methods
- Optical measurement and interference techniques
- RFID technology advancements
- AI and Big Data Applications
- Advanced Technologies in Various Fields
- Technology and Human Factors in Education and Health
University of Sassari
2016-2024
Polytechnic University of Turin
2023-2024
Abstract Background Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper to comparatively assess validate DMOs estimated using gait six different cohorts, focusing on sequence detection, foot initial contact detection (ICD), cadence (CAD) stride length (SL) estimates. Methods Twenty healthy older adults, 20 people Parkinson’s disease,...
Abstract This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and bout duration. The goal was provide recommendations on the use of devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Congestive Heart Failure, healthy older adults (n = 97) were monitored in laboratory (2.5 h), using lower back device. Two pipelines validated...
Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations quantifying digital outcomes (DMOs) both during supervised structured real-world conditions. The validity IMU-based methods the real-world, however, is still limited populations. Rigorous validation...
Introduction: Accurately assessing people’s gait, especially in real-world conditions and case of impaired mobility, is still a challenge due to intrinsic extrinsic factors resulting gait complexity. To improve the estimation gait-related digital mobility outcomes (DMOs) scenarios, this study presents wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units two distance sensors). Methods: The INDIP technical...
Abstract Wearable devices are used in movement analysis and physical activity research to extract clinically relevant information about an individual’s mobility. Still, heterogeneity protocols, sensor characteristics, data formats, gold standards represent a barrier for sharing, reproducibility, external validation. In this study, we aim at providing example of how (from the real-world laboratory) recorded from different wearables standard technologies can be organized, integrated, stored....
Background Wrist-worn inertial sensors are used in digital health for evaluating mobility real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, detection is an important step to identify regions interest where occurs, which requires robust algorithms due complexity arm movements. While exist other sensor positions, a comparative validation applied wrist position on data sets across different disease populations missing. Furthermore,...
Bluetooth Low Energy (BLE) is a wireless technology for exchanging data, over short distances, designed the Internet-of-Things era. As widely supported by wearable devices, BLE has potential to become an alternative indoor-localization and proximity sensing. The aim of this work was perform thorough characterization RSSI-distance relationship under controlled conditions using two devices. Four calibration models underwent comparative evaluation analysis. best results were obtained polynomial...
Background Gait characteristics are important risk factors for falls, hospitalisations and mortality in older adults, but the impact of COPD on gait performance remains unclear. We aimed to identify differences between adults with healthy age-matched controls during 1) laboratory tests that included complex movements obstacles, 2) simulated daily-life activities (supervised) 3) free-living (unsupervised). Methods This case–control study used a multi-sensor wearable system (INDIP) obtain...
Introduction The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis shifting unsupervised monitoring in naturalistic unconstrained settings. However, the extraction clinically relevant parameters from IMU data often depends heuristics-based algorithms rely empirically determined thresholds. These were validated small cohorts supervised Methods Here, a...
Gait analysis is commonly performed in standardized environments, but there a growing interest assessing gait also ecological conditions. In this regard, an important limitation the lack of accurate mobile gold standard for validating any wearable system, such as continuous monitoring devices mounted on trunk or wrist. This study therefore deals with development and validation new multi-sensor-based system digital assessment free-living particular, results obtained from five healthy subjects...
After a cerebral stroke, survivors need to follow neurorehabilitation program including exercises be executed under therapist's supervision or autonomously. Technological solutions are needed support the early discharge of patients just after primary hospital treatments, by still providing an adequate level rehabilitation. The DoMoMEA Project proposes fully-wearable m-health solution able administer therapy in patient's home every other place established patient for rehabilitation session....
There is growing interest in the quantification of gait as part complex motor tasks. This requires events (GEs) to be detected under conditions different from straight walking. study aimed propose and validate a new marker-based GE detection method, which also suitable for curvilinear walking step negotiation. The method was first tested against existing algorithms using data healthy young adults (YA, n = 20) then assessed 10 individuals following five cohorts: older adults, chronic...
Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim this study is to propose validate a protocol for simulating real-world gait accounting all these within single set observations, while ensuring minimisation participant burden safety.The included eight motor tasks at varying speed, incline/steps,...
Abstract Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices (WD) and ad-hoc algorithms, technical validation is still required. The aim of this paper to comparatively assess validate DMOs estimated using gait six different cohorts, focusing on sequence detection (GSD), foot initial contact (ICD), cadence (CAD) stride length (SL) estimates. Methods: Twenty healthy older adults, 20 people Parkinson’s disease,...
Stride length is often used to quantitatively evaluate human locomotion performance. by stride estimation can be conveniently obtained from the signals recorded using miniaturized inertial sensors attached feet and appropriate algorithms for data fusion integration. To reduce detrimental drift effect, different algorithmic solutions implemented. However, overall method accuracy supposed depend on optimal selection of parameters which are required set. This study aimed at evaluating influence...
Abstract Wearable technology has rapidly evolved, enabling the integration of various sensors and algorithms, opening new possibilities for context-aware applications in fields such as healthcare, fitness tracking, environmental monitoring. The discrimination between indoor outdoor environments is crucial. This often accomplished through technologies like GPS, Wi-Fi, cellular, Bluetooth. However, these methods have drawbacks, including privacy concerns, high power consumption, reliance on...
Abstract Background: Estimation of walking speed from wearable devices requires combining a set algorithms in single analytical pipeline. The aim this study was to validate pipeline for estimation and assess its performance across different factors (complexity, speed, bout duration) make recommendations on the use validity real-world mobility analysis. Methods: Participants with Parkinson's Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Congestive Heart...
Abstract Accurately assessing people’s gait, especially in real-world conditions and case of impaired mobility, is still a challenge due to intrinsic extrinsic factors resulting gait complexity. To improve the estimation gait-related digital mobility outcomes (DMOs) scenarios, this study presents wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units two distance sensors). The INDIP technical validity was...