Frailty is a common syndrome in older adults, marked by physiological reserve, which can lead to an increased vulnerability to stressors. This study aims to establish and validate a platform for simultaneous motor and cardiac function execution to evaluate motor and HR interaction, as a potential marker for frailty. Given the limitations of HR assessment during walking, such as motion artifacts, space constraints, and mobility restrictions, we utilized a validated upper extremity function (UEF) test. This test involves 20-second rapid elbow flexion, to assess motor performance. We hypothesized that using motor and HR interaction we would identify frailty with >80% accuracy. Older adults were recruited from three diverse cohorts. Inclusion included ability to walk, and exclusions included severe motor or cognitive impairments (MMSE≤23) and conditions affecting HR (e.g., arrhythmia and β-blocker). Frailty was classified using the Fried phenotype. For UEF, wearable motion sensors (100Hz) captured elbow angular velocity. HR was continuously recorded using a two-channel ECG system (1000Hz). The dynamic interconnection between angular displacement and HR was assessed, using convergent cross-mapping (CCM). CCM assesses the nonlinear directional interactions of variables in a complex dynamic system, based on state-space reconstruction of time series, and it is less biased to systems being nonlinear and nonstationary. Logistic regression models with demographics and CCM as independent variables, combined with 10-fold cross-validation, were used to identify frailty (pre-frail/frail vs. non-frail). 140 participants were recruited, including 26 non-frail (age=71.61±9.88), 93 pre-frail (age=77.55±9.46), and 21 frail (age=78.81±9.56) older adults. Using CCM, along with demographics, pre-frailty/frailty was identified with accuracy of 0.85 (sensitivity=77%, specificity=81%). This approach captures both cardiac and motor function in a clinical setting within less than two minutes of physical task while seated. These measures could be incorporated into accessible devices like smartwatches, enabling frailty assessment and remote monitoring in clinical and home settings.