Acceptability, Satisfaction, Usability, User Experience
Conditions
Keywords
Robotic platform, Monitoring system
Brief summary
Frailty is not related exclusively to age, but represents a state of increased biological and clinical vulnerability characterized by reduced functional reserve and greater susceptibility to adverse events, even in response to minor stress factors. In patients with complex conditions, such as severe acquired brain injuries, early detection and prompt treatment of clinical deterioration are essential to reduce the risk of acute readmission, complications, and in-hospital mortality. Many of these events are potentially predictable and preventable, given the presence of appropriate monitoring systems. Advanced care models, including early warning systems, have been developed to support healthcare professionals in identifying patients at risk by detecting significant changes in physiological parameters. In recent years, technological innovations-particularly in the fields of robotics and telemedicine-have created new opportunities to enhance clinical monitoring, enabling continuous data collection and more timely, proactive interventions. Social assistive robots are emerging as promising tools in healthcare settings. These systems can support clinicians and nurses in routine monitoring activities, help reduce workload, and facilitate more efficient and personalized care. By integrating robotic assistance with digital health platforms, it is possible to improve the quality and responsiveness of patient management, especially in high-complexity environments such as neurorehabilitation units. This study focuses on the use of an innovative robotic telemedicine system based on the integration of the MOVER-L prototype with the ROB.IN.CARE platform, owned by Item Oxygen Srl, which purchased the platform from the company CO-ROBOTICS S.R.L. through the PON SI-ROBOTICS project. The system is designed to continuously monitor patients' clinical conditions, collecting vital parameters and identifying early signs of deterioration. It supports healthcare professionals by providing real-time data and alerts, enabling earlier and more targeted interventions. The study is a low-intensity interventional clinical trial conducted in a Neurorehabilitation Unit. Patients with varying levels of clinical severity, classified according to the Glasgow Coma Scale, are enrolled and divided into two groups: a control group receiving standard care and an experimental group monitored using the robotic system in addition to usual care. The primary objective of the study is to evaluate the feasibility, usability, safety, and reliability of this robotic telemedicine solution in a real clinical setting. In addition, the study assesses its acceptability among both patients and healthcare professionals. These aspects are measured using validated tools, including the System Usability Scale (SUS) and the Health and Safety Executive Stress Scale (HSE), to understand the impact of the technology on user experience and workload. The integrated MOVER-L/ROB.IN.CARE system combines robotic assistance with continuous monitoring of vital signs and advanced software architecture. The platform incorporates predictive algorithms designed to stratify clinical risk and assess patient severity. It utilizes established clinical scoring systems, such as the Modified Early Warning Score (MEWS) for early detection of clinical deterioration, the quick Sequential Organ Failure Assessment (qSOFA) for sepsis risk evaluation, and the Kidney Disease: Improving Global Outcomes (KDIGO) criteria for the assessment of acute kidney injury. By enabling early identification of clinical worsening, the system aims to improve the timeliness and effectiveness of healthcare interventions, optimize clinical workflow, and reduce the risk of adverse events and complications. Ultimately, this study explores whether robotic telemedicine can represent a safe, feasible, and valuable tool to enhance the management of fragile patients in neurorehabilitation settings.
Interventions
DEVICERobotic platform monitoring system
The robot will observe patients and collect health data through clinical assessment scales including MEWS, qSOFA, and KDIGO, using the dedicated software application on a tablet. The data collected will then be processed to determine the patient's current risk status. If necessary, the robot will alert medical and nursing staff to the patient's condition in order to stabilize it as quickly as possible.
Sponsors
Ernesto Losavio
Item Oxygen
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
NONE
Intervention model description
Low-intensity interventional study
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Admission to the Neurorehabilitation Unit * Requirement for clinical monitoring and/or sub-intensive care * Ability to provide informed consent, or availability of a legally authorized representative to provide consent
Exclusion criteria
* No indication for intensive or sub-intensive clinical monitoring * Expected hospitalization duration insufficient to complete the study protocol * Participation in another clinical study that may interfere with the present study
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| HSE Stress Scale | At the end of treatment (1 week) | The Health and Safety Executive (HSE) Management Standards Indicator Tool is a validated questionnaire developed by the United Kingdom's Health and Safety Executive to assess work-related stress. It evaluates six key domains associated with workplace stress: demands, control, support, relationships, role, and change. The total score ranges from 38 to 190, with higher scores indicating lower levels of work-related stress (i.e., better working conditions). |
| System Usability Scale (SUS) | At the end of treatment (1 week) | The System Usability Scale (SUS) is a validated 10-item questionnaire used to assess the usability of a system. It evaluates users' perceived ease of use and satisfaction, reflecting the likelihood that the system will be accepted and used in the future. The total score ranges from 10 to 50, with higher scores indicating better perceived usability. The scale will be administered to nursing and medical staff. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Oxygen Saturation | From enrollment to the end of treatment at 1 week | Peripheral oxygen saturation (SpO₂) measured by pulse oximetry (%). |
| Heart Rate | From enrollment to the end of treatment at 1 week | Heart rate measured in beats per minute (bpm). |
| Pulse Rate | From enrollment to the end of treatment at 1 week | Pulse rate measured in beats per minute (bpm). |
| Diastolic Blood Pressure | From enrollment to the end of treatment at 1 week | Diastolic blood pressure measured in millimeters of mercury (mmHg). |
| Body Temperature | From enrollment to the end of treatment at 1 week | Body temperature measured in degrees Celsius (°C). |
| Respiratory Rate | From enrollment to the end of treatment at 1 week | Respiratory rate measured in breaths per minute (breaths/min). |
| Level of Consciousness (Glasgow Coma Scale) | From enrollment to the end of treatment at 1 week | Level of consciousness assessed using the Glasgow Coma Scale (GCS), with scores ranging from 3 to 15, where higher scores indicate better neurological status. |
| Hourly Urine Output | From enrollment to the end of treatment at 1 week | Urine output measured hourly, expressed in milliliters per hour (mL/hour). |
| Laboratory Parameters | From enrollment to the end of treatment at 1 week | Selected laboratory parameters will be assessed using standard clinical laboratory methods. Each parameter will be reported individually according to its specific unit of measure (e.g., mg/dL, mmol/L, g/L, or other relevant units depending on the parameter). |
Outcome results
None listed