This study aims to compare the physiologic stress experienced by the surgeon during unicompartmental knee arthroplasty (UKA) performed using a manual technique versus a computer-assisted technique. Surgeon physiologic parameters, including energy expenditure, heart rate, heart rate variability, and minute ventilation, will be measured intraoperatively using a wearable monitoring device (Hexoskin). The study seeks to determine whether computer-assisted surgery influences surgeon workload compared to the conventional manual approach.

Unicompartmental knee arthroplasty (UKA) is a widely performed surgical procedure for the treatment of unicompartmental knee osteoarthritis. Surgical techniques for UKA include conventional manual instrumentation and computer-assisted approaches, including navigation and robotic systems. While previous studies have evaluated clinical outcomes and implant positioning, limited data exist regarding the physiologic demands placed on the surgeon during these procedures.

Recent evidence has demonstrated that surgeon physiologic stress, including energy expenditure and cardiovascular parameters, can be objectively measured using wearable monitoring devices during total knee arthroplasty. However, no studies have specifically evaluated these parameters in the setting of UKA or compared manual and computer-assisted techniques.

The aim of this study is to prospectively evaluate and compare the physiologic workload of the surgeon during UKA performed using manual versus computer-assisted techniques. Surgeon physiologic parameters, including energy expenditure (kcal), heart rate (beats per minute), heart rate variability, and minute ventilation, will be continuously recorded intraoperatively using a validated wearable device (Hexoskin).

Patient demographic and surgical variables, including age, body mass index, and operative time, will also be collected to account for potential confounding factors. Statistical analysis will be performed to compare physiologic parameters between the two surgical techniques, with adjustment for relevant covariates.

The results of this study may provide objective data regarding surgeon workload and may contribute to a better understanding of the impact of surgical technology on operative demand and ergonomics.

Inclusion Criteria:

• primary, elective unicompartmental knee arthroplasty (UKA).
• Clinical and radiographic evidence of symptomatic unicompartmental knee osteoarthritis.
• Candidates for either manual or computer-assisted/robotic cemented UKA.
• Procedures performed by fellowship-trained arthroplasty surgeons to ensure technical consistency.
• Patients willing and able to provide informed consent for the collection of perioperative data.

Exclusion Criteria

• Revision Surgery: Patients undergoing revision knee arthroplasty (as the study focuses on primary cases).
• Complex Scars: Presence of significant prior knee surgery or hardware that may abnormally increase surgical difficulty.
• Inflammatory Arthritis: Patients with inflammatory conditions like rheumatoid arthritis (optional, depending on your focus).
• Non-elective or trauma-related knee procedures.
• Surgeon Limitation: Any physical condition of the participating surgeon that prevents the use of the wearable monitoring garment.

the study population consists of adult patients scheduled for elective, primary unicompartmental knee arthroplasty (UKA) at a high-volume orthopedic specialty center. This population includes individuals with symptomatic knee osteoarthritis limited to a single compartment (medial or lateral) who have failed conservative management. The cohort represents a broad range of body mass index (BMI) scores and age groups, reflecting the typical demographic of patients seeking partial knee replacement. Participants are selected based on the surgeon's clinical decision to utilize either a manual technique or a computer-assisted/robotic system, allowing for a real-world observational comparison of surgical physical demand.

De-identified individual participant data (including surgeon physiologic metrics and patient demographic variables) that underlie the results reported in the final article will be made available to researchers who provide a methodologically sound proposal.

Data will be available beginning 6 months and ending 36 months following article publication.

Data requests should be directed to xxonteduca85@gmail.com. To gain access, data requestors will need to sign a data access agreement.