Gait abnormalities are common in the elderly and individuals diagnosed with Parkinson’s, often leading to reduced mobility and increased fall risk. Monitoring and assessing gait patterns in these populations play a crucial role in understanding disease progression, early detection of motor impairments, and developing personalized rehabilitation strategies. In particular, by identifying gait irregularities at an early stage, healthcare professionals can implement timely interventions and personalized therapeutic approaches, potentially delaying the onset of severe motor symptoms and improving overall patient outcomes. In this paper, we studied older adults affected by chronic diseases and/or Parkinson’s disease by monitoring their gait due to wearable devices that can accurately detect a person’s movements. In our study, about 50 people were involved in the trial (20 with Parkinson’s disease and 30 people with chronic diseases) who have worn our device for at least 6 months. During the experimentation, each device collected 25 samples from the accelerometer sensor for each second. By analyzing those data, we propose a metric for the “gait quality” based on the measure of entropy obtained by applying the Fourier transform.

Telemedicine has emerged as a vital component of contemporary healthcare, revolutionizing the way medical services are delivered and accessed (e.g., it enables patients living in underserved or rural areas to receive medical consultation and treatment remotely). Moreover, telemedicine plays a pivotal role in improving healthcare efficiency by reducing wait times, minimizing unnecessary hospital visits, and optimizing resource allocation. In this paper, we present HealthTracker, a monitoring infrastructure for patients comprising two Internet of Things (IoT) devices (one of which was designed and created by us) and a mobile app that sends data collected by the IoT devices to a cloud service. All these components work together to provide an innovative system able to monitor patient health condition, provide alerts in emergency cases, and elaborate upon data to improve the quality of medical care. Preliminary tests show that the system works well, and real experimentation will start soon in collaboration with the local health authority.

Musculoskeletal disorders are common among older adults, affecting mobility and quality of life. Effective rehabilitation is essential, but the implementation of programs faces challenges. Traditional methods often necessitate in-person assessments, which can be difficult for older adults with mobility limitations. Telerehabilitation offers a solution, bringing therapy closer to patients. However, the accurate remote monitoring of health and performance remains a challenge. This study addresses this gap by developing and validating the System for Tracking and Evaluating Performance (STEP). STEP is a hardware-software system that automates physical performance tests, eliminating the need for constant expert supervision. The system focuses on three standard tests: the Six-Minute Walking Test (6MWT), the Ten-Meter Walking Test (10MWT), and the 30-s Sit-to-Stand Test (30STS). Validation compared results from the STEP app with in-person assessments by physicians for patients undergoing rehabilitation after knee or hip arthroplasty. The study found strong positive correlations between the app’s results and the physicians’ assessments for all tests. These findings demonstrate the STEP system’s potential as a reliable tool for remote physical performance assessment. Further research is needed to explore its integration into clinical practice and cost-effectiveness in reducing the need for operator assistance in monitoring patients with physical limitations.

The digitization of tourism has made numerous platforms available, but there remains a significant shortage of tools capable of promoting local events and activities. This study hypothesizes that a decentralized digital interface can mitigate over-tourism. We conducted an experiment by deploying a digital platform to assess the synergy between local providers and visitors through the Tourism Open-ended Experimentation Platform (TOEP), a multi-interface solution designed to directly connect tourism activity providers with residents and visitors. The platform integrates a web portal for providers and a mobile app for users, supported by a recommendation system based on individual profiles and preferences. TOEP stands out for its focus on local and sustainable tourism, facilitating the promotion of smaller events and helping to reduce the concentration of tourist flows in already saturated destinations. Initial validation, conducted with a panel of industry experts, highlighted the ease of use and good organization of the interfaces, with scores above average. Preliminary results confirm the relevance of TOEP as a tool for the sustainable and digitized promotion of local tourism, opening prospects for development towards a smart, participatory tourism ecosystem that can be replicated in different territorial contexts.