What is the Ability of Datamining Approaches to Cluster Patients With Idiopathic Neck Pain and Can Machine Learning Algorithms Provide More Efficient Rehabilitation and Less Recurrence Based on Kinaesthetic Training Protocols

Chronic idiopathic neck pain represents one of the most prevalent musculoskeletal conditions worldwide and is characterized by recurrent episodes, fluctuating symptom intensity, and frequent transition to persistent disability. While clinical management commonly focuses on short-term pain reduction, the more substantial societal burden arises from recurrence and chronicity rather than isolated acute episodes. Recurrent neck pain contributes to repeated healthcare consultations, prolonged work absenteeism, reduced productivity, and increasing healthcare expenditure. Despite the widespread use of exercise-based rehabilitation, recurrence rates remain high, suggesting that prevailing treatment approaches may insufficiently address the mechanisms underlying persistent dysfunction. As the prevalence of neck pain continues to rise across working-age populations, it is reasonable to question whether current rehabilitation models adequately target the neuromuscular and sensorimotor contributors to chronicity and repeated symptom exacerbations.

Most individuals presenting for physical therapy are diagnosed with non-specific or idiopathic neck pain, a broad category encompassing heterogeneous clinical presentations with variable combinations of pain, stiffness, dizziness, visual disturbances, and impaired movement control. Patients may differ substantially in movement strategies, proprioceptive acuity, neuromuscular coordination, and adaptive motor patterns, yet they are frequently managed using standardized exercise protocols. Conventional clinical assessment tools are effective in distinguishing patients from asymptomatic individuals but provide limited resolution for identifying meaningful subgroups within the idiopathic neck pain population. Over the last decade, patient-centered evaluation in spinal disorders has frequently relied on numerical pain rating scales and disability questionnaires, while comparatively less emphasis has been placed on objective assessment of neuromuscular control mechanisms that may drive chronicity. Emerging evidence demonstrates that individuals with a history of neck pain exhibit persistent alterations in sensorimotor function even during symptom remission, implying that underlying neuromuscular adaptations may predispose individuals to recurrence and reduced resilience to mechanical or psychosocial stressors.

Cervical sensorimotor control, often conceptualized as cervicocephalic kinaesthetic awareness, integrates proprioceptive input from cervical musculature and joint mechanoreceptors with visual and vestibular information to coordinate accurate head positioning and smooth eye-head movements. Altered cervical afferent input can disrupt this integration, leading to inaccurate movement perception, impaired position sense, and maladaptive motor output strategies. Prolonged proprioceptive disturbances may induce central neural plasticity changes within brainstem and cortical sensorimotor networks, potentially sustaining dysfunction beyond the initial pain episode and contributing to the maintenance of chronic symptoms. Systematic reviews report variable findings regarding the magnitude of kinaesthetic impairments in neck pain populations, likely reflecting recruitment heterogeneity, differences in symptom duration, and variability in functional deficits. These inconsistencies underscore the importance of multidimensional characterization of sensorimotor performance rather than reliance on isolated parameters or single test outcomes.

Kinaesthetic training targeting movement accuracy, proprioceptive recalibration, and coordinated motor output has demonstrated clinically meaningful short-term improvements in pain and disability, with some effects persisting for several months. However, approximately one third of patients fail to demonstrate improvement in pain intensity or disability, and nearly half do not exhibit measurable gains in objective kinematic performance variables. Additionally, dropout rates of up to twenty percent have been reported, frequently attributed to discomfort, fatigue, or symptom aggravation during exercises that challenge impaired sensorimotor systems. These observations suggest that uniform rehabilitation protocols may not optimally address individualized neuromuscular profiles and that subgroup-specific interventions may enhance treatment responsiveness, improve adherence, and reduce variability in outcomes.

Cervical movement control involves coordinated interaction between proprioceptive, vestibular, and visual systems. Movement tasks performed at varying amplitudes and velocities challenge different components of sensorimotor processing and may reveal distinct deficit patterns. Slow, large-amplitude movements increase reliance on proprioceptive discrimination and smoothness regulation, often reflected in elevated jerk index values when coordination is impaired. Faster movements may engage vestibular-dependent mechanisms and dynamic stability control. Furthermore, altered afferent input from cervical muscles can influence adaptive plastic changes in vestibular-dependent motion sensitivity, potentially affecting head and neck control at higher movement velocities. Consequently, assessment and training should incorporate movements across multiple amplitudes and velocities to adequately capture subgroup-specific impairments.