Chaos and Nonlinear Time-series Analysis of Finger Pulse Waves for Depression Detection

Depressive disorders are mental illnesses that can severely affect one’s health and well-being. If depression is not early detected and left untreated, it can consequently lead to suicide. This paper presents for the first time a novel combination of chaos theory and nonlinear dynamical analysis of signal complexity of photoplethysmography waveforms for detection of depression. Experimental results obtained from the analysis of mentally disordered and control subjects suggest the potential application of the proposed approach.

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