Goal: The clinical investigation aims to evaluate the impact of orthopedic shoulder surgery on sleep quality and functional recovery in workers with shoulder musculoskeletal disorders. This will be assessed through validated questionnaires and physiological monitoring using wearable sensors.

Participant Population: The study will enroll at least 30 participants diagnosed with shoulder musculoskeletal disorders, such as rotator cuff tears, adhesive capsulitis, and glenohumeral osteoarthritis. Participants must be employed in physically demanding jobs that require frequent upper limb activity and are scheduled for orthopedic shoulder surgery.

Main Questions:

• How does post-operative rehabilitation influence sleep quality and functional recovery in workers with shoulder musculoskeletal disorders?
• To what extent does post-operative rehabilitation improve pain management and overall quality of life in these patients?
• How do patients perceive the usability and comfort of wearable sensors during their rehabilitation process?

Participant Tasks:

• Initial Assessment: Comprehensive clinical evaluation, including demographic and anthropometric data collection, and administration of the Pittsburgh Sleep Quality Index (PSQI).
• Wearable Sensor Training: Instruction on the proper use of the Medtronic Zephyr BioPatch™ wearable biosensor for monitoring physiological and postural signals.
• Sleep Monitoring: Participants will undergo sleep assessments at three key time points: Two nights before surgery (baseline measurement); Two weeks post-surgery during early rehabilitation; 30 days into the rehabilitation program.
• Daily Logging: Completion of the Consensus Sleep Diary each morning following sensor use.
• Functional Assessment: Objective evaluation of shoulder functionality through validated clinical scales and range of motion (ROM) assessments.
• Pain and Usability Evaluation: Measurement of pain reduction and usability of wearable technology using Patient-Reported Outcome Measures (PROMs).

Shoulder pain represents one of the most widespread musculoskeletal issues globally, significantly impacting workers' quality of life and productivity. This condition often leads to substantial consequences for the overall health of affected individuals, with notable effects on essential aspects such as sleep. The majority of workers with shoulder pain also experience sleep disturbances, ranging from mild discomfort to complete inability to sleep. Nighttime pain, insomnia, and the inability to sleep on the affected side are factors that negatively impact patients' sleep quality. Poor sleep quality, in addition to pain, is one of the most common symptoms that drive patients to seek treatment and, if necessary, consider undergoing surgery.

Several studies have highlighted that rehabilitation following orthopedic surgery can significantly influence patients' sleep quality. Various patient-reported outcome measures (PROMs) have been introduced to assess improvements in sleep during the rehabilitation process. An example of a PROM is the Pittsburgh Sleep Quality Index (PSQI). With the growing interest in understanding the association between post-operative rehabilitation and sleep patterns, technologies have been introduced to provide objective and quantitative measures of these changes.

The gold standard for studying sleep is polysomnography, which, due to its intrusive nature, can alter the sleep quality and profile for reasons unrelated to the surgical rehabilitation itself. Recent studies have shown that wearable sensors measuring physiological parameters (e.g., ECG, HRV) and posture, combined with advanced artificial intelligence techniques, offer the possibility to monitor sleep profiles with good reliability in a non-intrusive and real-time manner.

This study aims to use non-invasive wearable sensors and artificial intelligence algorithms to monitor patients undergoing post-operative rehabilitation following shoulder surgery. The objective is to explore in-depth the variations in sleep patterns and quality during the rehabilitation process, analyzing the relationship between sleep and recovery. This research seeks to empirically demonstrate the benefits of post-operative rehabilitation on improving the sleep quality and profile of patients with shoulder disorders.

This research is of critical importance as it provides essential insights for clinicians and workers regarding the impact of rehabilitation on sleep quality. Understanding the relationship between shoulder pain, rehabilitation, and sleep disturbances is a key clinical issue. The outcomes of this study could have significant implications for the overall management of shoulder pain, potentially enhancing clinical practices and improving healthcare for individuals affected by these conditions. In addition, this research aims to offer valuable information that will inform optimal treatment strategies, ultimately enhancing workplace productivity and overall health.

Inclusion Criteria

• Informed consent obtained.
• Age ≥ 18 years.
• Good understanding of spoken and written Italian.
• Diagnosis of shoulder musculoskeletal disorders.
• Employment in a physically demanding job requiring frequent upper limb activity.
• Workers scheduled to undergo orthopedic shoulder surgery.
• Workers who have accepted the surgical treatment.

Exclusion Criteria

• Patients with sleep disorders.
• Patients undergoing pharmacological treatments that could potentially affect sleep patterns (e.g., antidepressants, hypnotics, and stimulants).
• Failure to sign informed consent.
• Patients with neuromuscular diseases.

The ownership of the data is of the promoter and shared with the investigators and will be managed according to the agreements between the participating institutions and with the researchers. Data Property belongs to Fondazione Policlinico Universitario Campus Bio-Medico. The personnel involved in this study will have access to all data. In agreement with the ICH-GCP, the principal investigator of the study agrees to produce a report on the study, share all the data collected as described in the Protocol, and ensure that the data are reported responsibly and consistently.

The transmission or dissemination of data through scientific publications and/or presentations in congresses, conferences, seminars, and participation in multicenter studies will take place exclusively following a purely statistical processing of the same, or in any case, in an anonymous form.