Abstract: A method for detecting the onset of drowsiness in an operator of a vehicle or other apparatus. The operator grips a steering wheel or similar control handle, which continuously outputs gripping signals. The method provides for dynamic offset removal to obtain baseline signals, selection of physiologically-significant signals, combining and processing signals to form a proxy signal, analysis of the proxy signals to detect patterns indicative of the onset of drowsiness, and generating alerts as appropriate. The method provides for multiple sliding windows, for dynamic baseline adjustment; and statistical processing to detect physiologically-meaningful patterns indicative of the onset of drowsiness, as distinct from incidental changes in operator gripping through hand position readjustment during normal operation.

Abstract: A method for detecting sleep-related Apneas, Hypopneas, heart rate, body movements, and snoring events of a sleeping person. An online, adaptive detection system conditions and automatically analyzes physiological, movement-related and ambient acoustical signals to count valid snoring events, non-breathing events and calculates patient AHI (Apnea Hypopnea Index). Patient respiration, snoring, movements, presence and heart rate are continuously monitored, recorded and transmitted without requiring any sensors, electrodes, leads, cuffs, or cannulas to be attached to the patient. Additional benefits include improving the reliability of Apnea/Hypopnea detection in the patient home environment, and utilizing the method and the device for Apnea/Hypopnea and snoring positional therapy.

Abstract: A method for detecting the onset of drowsiness in an operator of a vehicle or other apparatus. The operator grips a steering wheel or similar control handle, which continuously outputs gripping signals. The method provides for dynamic offset removal to obtain baseline signals, selection of physiologically-significant signals, combining and processing signals to form a proxy signal, analysis of the proxy signals to detect patterns indicative of the onset of drowsiness, and generating alerts as appropriate. The method provides for multiple sliding windows, for dynamic baseline adjustment; and statistical processing to detect physiologically-meaningful patterns indicative of the onset of drowsiness, as distinct from incidental changes in operator gripping through hand position readjustment during normal operation.

Abstract: A method and system for detecting the physiological onset of operator fatigue. The condition of the operator is correlated with physiological signs of the early stages in the process of falling asleep according to the Hori EEG model. Passive correlation is done via monitoring of the gripping pressure of the operator's hand(s) on a handgrip containing pressure transducers. Correlation with Hori stage 2 is a preliminary indicator of the onset of operator fatigue. Active correlation is done via contingent Psychomotor Vigilance Tests administered upon the preliminary indication, with operator stimulus from a vibratory element in the handgrip and operator response being a rapid increase in gripping pressure. Correlation of the frequency of contingent PVT requests with Hori stage 3 is a critical indicator of the onset of operator fatigue. Upon detection of the onset of fatigue, an alarm is signaled to the operator and other personnel.