Integration of a Robotic Platform for Clinical Monitoring of Patients With Severe Acquired Brain Injury in High-Intensity Care Units

NCT07496346 | Not Yet Recruiting

• 1 other identifier: 7902
• Study Type: interventional
• Target: 12
• Locations: 0 countries
• Sites: N/A

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, promoted by Item Oxygen (Bari, Italy). 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.

Conditions

User Experience; Usability; Acceptability; Satisfaction

Keywords

Robotic platform; Monitoring system

Outcome Measures

Primary Outcomes (2)

• HSE Stress Scale

  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).

  At the end of treatment (1 week)

• System Usability Scale (SUS)

  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.

  At the end of treatment (1 week)

Secondary Outcomes (9)

• Oxygen Saturation

  From enrollment to the end of treatment at 1 week

• Heart Rate

  From enrollment to the end of treatment at 1 week

• Pulse Rate

  From enrollment to the end of treatment at 1 week

• Diastolic Blood Pressure

  From enrollment to the end of treatment at 1 week

• Body Temperature

  From enrollment to the end of treatment at 1 week

Study Arms (2)

Experimental Group

EXPERIMENTAL

The experimental group will undergo monitoring with the robotic platform.

Device: Robotic platform monitoring system

Control Group

NO INTERVENTION

The control group will undergo the routine medical and nursing evaluations and measurements as per standard clinical practice.

Interventions

Robotic platform monitoring system DEVICE

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.

Also known as: robotic platform, monitoring system

Experimental Group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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

You may not qualify if:

• 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

Sponsors & Collaborators

• Ernesto Losavio: lead
• Item Oxygen: collaborator

MeSH Terms

Conditions

Personal Satisfaction

Condition Hierarchy (Ancestors)

Behavior

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: SUPPORTIVE CARE
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Director of the Neurorehabilitation and Spinal Unit, ICS Maugeri IRCCS Bari, Italy

Model Details: Low-intensity interventional study

Study Record Dates

• First Submitted: March 19, 2026
• First Posted: March 27, 2026
• Study Start: May 1, 2026
• Primary Completion (Estimated): November 1, 2026
• Study Completion (Estimated): November 1, 2026
• Last Updated: April 22, 2026

Record last verified: 2026-04