Age-based model for metacarpophalangeal joint proprioception in elderly

Abstract

Neurological injuries such as stroke can lead to proprioceptive impairment. For an informed diagnosis, prognosis, and treatment planning, it is essential to be able to distinguish between healthy performance and deficits following the neurological injury. Since there is some evidence that proprioception declines with age and stroke occurs predominantly in the elderly population, it is important to create a healthy reference model in this specific age group. However, most studies investigate age effects by comparing young and elderly subjects and do not provide a model within a target age range. Moreover, despite the functional relevance of the hand in activities of daily living, age-based models of distal proprioception are scarce. Here, we present a proprioception model based on the assessment of the metacarpophalangeal joint angle difference threshold in 30 healthy elderly subjects, aged 55-80 years (median: 63, interquartile range: 58-66), using a robotic tool to apply passive flexion-extension movements to the index finger. A two-alternative forced-choice paradigm combined with an adaptive algorithm to define stimulus magnitude was used. The mixed-effects model analysis revealed that aging has a significant, increasing effect on the difference threshold at the metacarpophalangeal joint, whereas other predictors (eg, tested hand or sex) did not show a significant effect. The adaptive algorithm allowed reaching an average assessment duration <15 minutes, making its clinical applicability realistic. This study provides further evidence for an age-related decline in proprioception at the level of the hand. The established age-based model of proprioception in elderly may serve as a reference model for the proprioceptive performance of stroke patients, or of any other patient group with central or peripheral proprioceptive impairments. Furthermore, it demonstrates the potential of such automated robotic tools as a rapid and quantitative assessment to be used in research and clinical settings.

Keywords: MCP; aging; difference threshold; hand function; joint position sense; presbypropria; robotic assessment; somatosensation.

Figure 1

Side view on the RCM mechanism of the robotic device used to induce passive movements around the MCP joint. Note: The sequence of pictures shows one trial, during which two different flexion angles (A1 and A2) are presented. Abbreviations: MCP, metacarpophalangeal; RCM, remote center of motion.

Figure 2

Resulting psychometric functions and PEST sequences of a representative subject. Notes: (Top) Psychometric functions (thick lines) for both hands of subject S22 (67-year-old male). The size of the black dots indicates the number of presentations of a stimulus at a certain stimulus level (Δ stimulus). (Bottom) Corresponding PEST sequences for the same subject. The thick line represents the stimulus level at each trial. Abbreviations: DL, difference threshold or limen; PEST, Parameter Estimation by Sequential Testing.

Figure 3

Age–DL relationship. Notes: Aging has a significant increasing effect on the DL (P<0.05). The DL of the dominant hand is indicated by an upward-pointing triangle and the DL of the nondominant by a downward-pointing triangle. Both assessments are connected through a gray vertical line for each subject. Black lines show the age-based DL model (thick line) ±SE (dashed lines) obtained from the mixed-effects model analysis. Abbreviations: DL, difference threshold or limen; SE, standard error.