| CPC A61B 5/165 (2013.01) [A61B 5/4884 (2013.01); A61B 3/113 (2013.01); A61B 5/0205 (2013.01); A61B 5/021 (2013.01); A61B 5/024 (2013.01); A61B 5/0533 (2013.01); A61B 5/0816 (2013.01); A61B 5/1116 (2013.01); A61B 5/14542 (2013.01); A61B 5/318 (2021.01); A61B 5/369 (2021.01); A61B 5/442 (2013.01); A61B 5/4803 (2013.01)] | 22 Claims |
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1. A computer-implemented method for recording daily life patterns, behavior and function observations of individuals in varied settings over a specific time period, or a mental health episode to improve treatment of mental illnesses of the individuals, said method comprising:
using a device chosen from the group of portable devices and wearable multi-sensor data fused devices, the device comprising audio-visual cameras and sensors that are operable to monitor and record vital parameters, sleep patterns and self-reported changes of an individual, the device and the audio-visual cameras and the sensors thereof being controlled by at least one processor of a system of hardware to acquire biometric and physiological parameters and speech content and verbal communication responses of the individual to record a mental health episode as and when the individual experiences the mental health episode or with stimuli loaded by a clinician based upon specific disorders or a diagnosis of the individual;
presenting the stimuli to the individual through visual, oral, aural, kinesthetic, and/or written methods;
obtaining, using the sensors, an initial set of objective data that quantify a set of the biometric and physiological parameters and recording, using the audio-visual cameras, an initial set of the speech content and verbal communication responses of the individual to the stimuli loaded by the clinician;
generating and visualizing, using the at least one processor of the system of hardware, the initial set of the objective data;
repeating the obtaining step to obtain, using the sensors, subsequent sets of the objective data that quantify subsequent successive sets of the biometric and physiological parameters and to record, using the audio-visual cameras, subsequent successive sets of the speech content and verbal communication responses of the individual to subsequent successive sets of the stimuli that are selected and administered by the clinician and presented to the individual;
repeating the generating and visualizing step, using the at least one processor of the system of hardware, to generate and visualize the subsequent successive sets of the objective data;
transferring, using the at least one processor of the system of hardware, the initial and subsequent successive sets of the objective data to a database to produce an individual record containing the initial and subsequent successive sets of the objective data;
quantitatively comparing, using the at least one processor of the system of hardware or within the database, the initial and subsequent successive sets of the objective data contained in the individual record to detect changes in the biometric and physiological parameters, and quantitatively comparing, using the at least one processor of the system of hardware, recordings of the initial and subsequent successive sets of the speech content and verbal communication responses of the individual to detect changes in tone fluctuations, tone perturbations, speech rate, speech patterns, and linguistic content of the individual corresponding to changes in at least one mental health condition of the individual;
processing, using the at least one processor of the system of hardware or within the database, the objective data of the initial and subsequent successive sets of the objective data to classify the biometric and physiological parameters and the speech content and verbal communication responses of the individual as multidimensional feature data comprising features, use data analytics, mathematical tools, and machine learning algorithms in real time to extract and divide the features of the multidimensional feature data into clusters, and perform pattern classification on the clusters to extract a mental state of the individual;
creating, using the at least one processor of the system of hardware, a risk classification and a visualization of the multidimensional feature data, the pattern classification, and the clusters based upon severity of the mental state of the individual; and
generating illness condition and information of the individual by integrating the changes in the biometric and physiological parameters and the speech content and verbal communication responses of the individual and inferences drawn by the device from daily activities, daily life patterns, behavior and function observations of the individual in varied settings over a specific time period or during the mental health episode, from a mental health examination of the individual, from a diagnosed illness and conditions information of the individual, from medical histories of the individual, and from changes in the medical histories of the individual.
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