Advancing Rotator Cuff Tear Management: How Kinematic Analysis Enhances Diagnosis and Treatment

Ashish Gupta, MBBS, MSc, FRACS, FAORTHOA, AUSTRALIA Anna Moyle Thomson, Bachelor of Physiotherapy (Hons), AUSTRALIA Terence Felix, MPH, BSc, MD student, AUSTRALIA

ISAKOS eNewsletters   Current Perspective 2025   Not yet rated

Introduction

Rotator cuff tears (RCTs) are a major contributor to shoulder dysfunction globally, affecting both older populations and overhead athletes. Despite advances in surgical repair, many patients with RCTs continue to experience persistent dysfunction. The underlying problem is often not purely structural—it’s functional. While many tears remain asymptomatic, symptomatic full-thickness RCTs can result in substantial deficits in range of motion (ROM), strength, and coordination. The loss of coordinated cuff function leads to altered glenohumeral (GH) mechanics, resulting in compensatory overactivation of muscles such as the deltoid and trapezius. These changes can cause pain, inefficiency, and reduced functional capacity.

For orthopaedic surgeons, treatment decisions are often guided by physical examination and imaging findings (e.g., MRI). However, these tools lack dynamic insight and cannot fully differentiate between weakness, stiffness, neuromuscular inhibition, and chronic compensatory patterns. With the growing emphasis on personalised and value-based care, objective tools that assess real-time function are becoming essential.

At the Queensland Unit for Advanced Shoulder Research (QUASR) at Queensland University of Technology (QUT) in Brisbane, Australia, our laboratory utilises a multimodal platform that combines surface electromyography (EMG), inertial measurement units (IMUs), and marker-based 3D motion capture to evaluate shoulder biomechanics before and after surgery. These technologies provide clinicians with actionable data that can improve diagnostic precision, inform surgical planning, and enhance postoperative rehabilitation.

Limitations of Traditional Diagnostic Approaches

The standard diagnostic toolkit for RCTs includes clinical tests (e.g., Jobe, Neer, Hawkins), imaging (MRI or ultrasound), and patient-reported symptoms. While essential, these assessments offer static snapshots of pathology. They fail to assess movement quality, coordination, or compensation—factors that are especially critical in patients with chronic cuff pathology or equivocal imaging findings.

Motion analysis bridges this gap by capturing kinematic and muscular patterns during active movement. This allows clinicians to visualise dysfunction that might be overlooked in traditional assessment and supports more informed decision-making, particularly in cases in which compensation may mask actual impairment.

Motion analysis integrates the following technologies to assess shoulder mechanics and muscular control:

• 3D Marker-Based Motion Capture: An optical system with reflective markers to track shoulder, scapular, and thoracic movement during upper limb clinical and functional tasks. This system segments GH and scapulothoracic (ST) contributions to overall shoulder movement.
• Surface EMG: Electrodes are placed over key muscles (deltoid, upper trapezius, infraspinatus, pectoralis major, biceps, triceps) to examine activation, timing, amplitude, abnormal co-contraction or compensation patterns.
• Inertial Measurement Units (IMUs): Wearable sensors that provide data on angular velocity, movement smoothness, and dynamic shoulder mechanics.

Together, these tools provide real-time insights into shoulder biomechanics, enabling clinicians to personalise surgery planning and track functional recovery.

Figure 1. Motion analysis setup using marker-based 3D motion capture, IMUs, and surface EMG. Markers and sensors are placed on key anatomical landmarks and muscles to assess joint kinematics and activation. IMUs are positioned on the sternum, clavicle, acromion, humerus, forearm, and hand.

Observations

At QUASR, we are currently conducting a longitudinal study evaluating shoulder biomechanics and early preoperative trends in patients with chronic RCTs. Two common compensatory movement patterns during shoulder flexion are revealed:

1. Increased Scapular Compensation: Greater upward rotation and posterior tilt of the scapula, especially in mid-range elevation, suggesting reliance on scapulothoracic motion to achieve functional reach.
2. Reduced Glenohumeral Contribution: Reduced GH elevation and angular velocity. In severe cases, patients exhibit trunk lean and scapular elevation to complete functional and clinical tasks.

Surface EMG recordings indicate increased activation of the upper trapezius and disrupted coordination in the posterior cuff musculature. These findings highlight the value of real-time motion analysis in identifying patient-specific compensations—insights not captured by static imaging or conventional ROM testing.

Figure 2. This figure presents preoperative data during forward shoulder elevation in a patient with chronic RCTs. Left side of image: The joint angle graph (bottom left panel) demonstrates reduced overall humerothoracic (HT) elevation and diminished glenohumeral (GH) contribution, with increased compensatory scapular motion relative to the contralateral, healthy side (not shown). Right side of image: EMG traces display peak muscle activity as a percentage of maximum voluntary contraction (%MVC), including the anterior, middle, and posterior deltoid (left column), and pectoralis major, upper trapezius, and infraspinatus (right column). These patterns reflect compensatory recruitment strategies associated with chronic rotator cuff dysfunction.

Evidence from the Literature: Functional Consequences of RCTs

Several studies reinforce the clinical significance of dynamic kinematic assessment in patients with RCTs:

Kolk et al. (2017) used 3D motion capture to show:

• Reduced GH elevation and external rotation
• Increased scapular upward rotation and posterior tilt in massive posterosuperior RCTs
• Highlighted the critical role of infraspinatus in preserving function.

Robert-Lachaine et al. (2016) also employed 3D motion capture and reported:

Decreased scapulohumeral rhythm in symptomatic RCTs

Greater ST compensation, especially in patients with <90° active elevation

Overall disruption in shoulder coordination

These findings support the use of dynamic motion analysis to capture both neuromuscular adaptation and structural deficits in RCT patients.

Figure 3. Scapulohumeral rhythm comparison between healthy controls and RCT patients (Robert-Lachaine et al., 2016). RCT patients exhibit altered rhythm and greater ST compensation, especially during early and mid-range elevation.

Using IMUs to Quantify Shoulder Dysfunction

IMUs are emerging as accessible tools for functional screening and follow-up.

Kwak et al. (2020) introduced a portable IMU-based shoulder assessment protocol and demonstrated that patients with RCTs exhibited:

• Significantly lower angular velocities
• Reduced motion smoothness during active elevation
• Clear differentiation from healthy controls

These metrics correlated with clinical symptoms and can help to identify dysfunction that is not apparent on imaging alone. IMU data may support surgical timing, track rehabilitation progress, and aid in return-to-activity decisions.

Figure 4. Velocity profiles during arm elevation in healthy subjects (left) vs. RCT patients (right) (Kwak et al., 2020). RCT patients exhibited fragmented, erratic angular velocity with more peak points, indicating impaired smoothness of motion.

Figure 5. Clinical application of IMUs for shoulder assessment. Sensors on the upper limb and trunk record motion quality to distinguish normal and pathological movement (Kwak et al., 2020).

Improving Surgical Planning with Motion Analysis

Beyond diagnosis, kinematic analysis offers tangible benefits for surgical planning:

Kolk et al. (2016) found that scapular kinematics tended to normalise after repair, especially in patients with preserved infraspinatus function—supporting the use of preoperative kinematic screening

Henseler et al. (2017) compared teres major vs. latissimus dorsi tendon transfers in patients with irreparable posterosuperior RCTs using 3D motion capture. Findings demonstrated:

• Improved ROM and patient function in both groups
• Teres major transfers led to more lateral scapular rotation
• The use of 3D motion capture can guide transfer selection based on individual biomechanical needs.

Such insights are invaluable for complex surgical planning—whether evaluating repairability, selecting tendon transfers, or managing expectations in cases of partial repair.

Postoperative Monitoring and Rehabilitation

Traditional postoperative monitoring often relies on patient-reported outcome measures (PROMs) and clinic-based ROM assessments. While useful, these tools can lack sensitivity and are prone to subjectivity and reporting bias. They also fail to capture compensatory strategies or subtle deficits in movement quality that may persist after surgery.

Motion analysis offers a more objective, data-driven alternative. With technologies such as 3D motion capture, IMUs, and EMG, we can:

• Quantitatively track recovery over time
• Identify persistent compensations (e.g., trunk lean, shoulder shrug) during both clinical and functional tasks
• Stratify patients who may benefit from extended or targeted rehabilitation
• Establish more accurate return-to-function milestones

In our ongoing study, patients are assessed at multiple time points, including preoperatively and again at 6 and 12-months postoperatively, using our full-motion analysis platform.

Provisional Findings:

• Improved humerothoracic motion and increased glenohumeral contribution during forward elevation are anticipated by 6 months postoperatively
• Scapular dyskinesis and upper trapezius overactivation are expected to begin normalising, though may continue to evolve beyond the early recovery phase
• Persistent compensatory movement patterns may remain in some patients, potentially correlating with delayed functional recovery or lower satisfaction outcomes

These insights enable us to assess surgical success not only based on tendon integrity or static clinical exams, but also on the restoration of efficient, coordinated movement—an essential goal for achieving long-term outcomes and serving high-demand patients.

Clinical Integration and Future Directions

While high-end motion labs may not be feasible in every orthopaedic practice, scalable versions of these technologies are emerging:

• Clinic-Based IMUs can be used for efficient ROM screens and objective functional assessments
• Markerless Capture Apps may soon integrate with electronic medical records, offering streamlined workflows
• AI-Driven Analytics may soon identify patterns across populations to benchmark outcomes and personalise care

As this technology becomes more accessible, orthopaedic surgeons will be empowered with data to:

• Tailor surgical strategies to individual kinematics
• Set targeted rehabilitation goals
• Track recovery with objective metrics.
• Contribute to multicentre databases tracking shoulder outcomes globally

Conclusion

3D motion capture and wearable technologies are redefining shoulder care. By integrating EMG, IMUs, and 3D motion capture systems, clinicians can move beyond structural assessments and toward functional, patient-specific care.

For orthopaedic surgeons, this represents a shift toward more precise, data-informed care, improving surgical planning, rehabilitation, and long-term outcomes in the management of rotator cuff tears.

References

1. Kolk A, Henseler JF, De Witte PB, Van Zwet EW, Van Der Zwaal P, Visser CPJ, et al. The effect of a rotator cuff tear and its size on three-dimensional shoulder motion. Clin Biomech. 2017;45:43–51.
2. Robert-Lachaine X, Allard P, Godbout V, Tétreault P, Begon M. Scapulohumeral rhythm relative to active range of motion in patients with symptomatic rotator cuff tears. J Shoulder Elbow Surg. 2016;25(10):1616–1622.
3. Henseler JF, Kolk A, Zondag B, Nagels J, De Groot JH, Nelissen RGHH. Three-dimensional shoulder motion after teres major or latissimus dorsi tendon transfer for posterosuperior rotator cuff tears. J Shoulder Elbow Surg. 2017;26(11):1955–63.
4. Kolk A, De Witte PB, Henseler JF, Van Zwet EW, Van Arkel ERA, Van Der Zwaal P, et al. Three-dimensional shoulder kinematics normalise after rotator cuff repair. J Shoulder Elbow Surg. 2016;25(6):881–9.
5. Kwak JM, Ha TH, Sun Y, Kholinne E, Koh KH, Jeon IH. Motion quality in rotator cuff tear using an inertial measurement unit: new parameters for dynamic motion assessment. J Shoulder Elbow Surg. 2020;29(3):593–9.

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