System and method for multi-modal neurological and health assessment

A method for providing an assessment of a neurological condition of a subject, the method comprising:

• using a plurality of sensors configured to collect biometric data from the subject;
• using at least one processor coupled to the sensors to receive biometric data;
• using a data collection module configured to store the collected biometric data;
• and
• using a neural assessment module configured to:
• extract a plurality of physiological signals from the stored biometric data;
• generate one or more neurological risk scores using machine learning models trained on neurological data;
• and
• produce personalized health recommendations based on the risk scores.

A system for providing an assessment of a neurological condition of a subject, the system comprising:

• at least one processor configured to receive and analyze data from a plurality of sensors, wherein the sensors comprise biometric sensors, speech sensors, blood sample sensors, wearable sensors, sleep sensors, exercise sensors, stress sensors, heart rate sensors, and diet sensors;
• a data collection module configured to store the received data from the sensors;
• a neural assessment module configured to:
• adaptively extract a plurality of signals associated with neural parameters of the subject from the data collection module, wherein the signals include speech recordings, biomarker data, and wearable data;
• dynamically generate one or more neurological risk scores for the subject based on the plurality of signals using machine learning models, wherein the risk scores indicate a probability that the subject suffers from a neurological condition;
• automatically adjust selection of the neural parameters based on the risk scores;
• compare a prior clinical assessment to the risk scores to check for false positives or negatives;
• compute a confidence index for recurring questions posed to the subject and/or a caregiver of the subject;
• generate predicted improvements in the risk scores based on care recommendations, which are selected to reduce the risk scores;
• compute trends in the risk scores to determine additional recommendations;
• reserve care resources based on the risk scores;
• generate mortality, morbidity, and brain pathology indicators based on the risk scores;
• generate risk scores for the caregiver based on the subject's risk scores;
• extract signals from the sensors including biochemical, GPS, respiratory, cardiac, neurological, motion, augmented reality, and blood pressure sensors;
• analyze the speech recordings for linguistic biomarkers indicative of neurological health;
• analyze blood biomarkers associated with neurological diseases;
• analyze wearable data for symptoms and behaviors indicative of neurological health;
• generate a lifestyle assessment analyzing sleep, exercise, stress, heart health, and diet data;
• and
• produce personalized recommendations based on the neurological and lifestyle assessments.

A method for providing an assessment of a neurological condition of a subject, comprising:

• collecting data from biometric, speech, blood, wearable, sleep, exercise, stress, cardiac, and diet sensors;
• storing the received data from the sensors in a data collection module;
• adaptively extracting, by a neural assessment module, a plurality of signals associated with neural parameters of the subject from the data collection module, wherein the signals include speech recordings, biomarker data, and wearable data;
• dynamically generating, by the neural assessment module, one or more neurological risk scores for the subject based on the plurality of signals using machine learning models, wherein the risk scores indicate a probability that the subject suffers from a neurological condition;
• automatically adjusting selection of the neural parameters based on the risk scores;
• comparing a prior clinical assessment to the risk scores to check for false positives or negatives;
• computing a confidence index for recurring questions posed to the subject and/or caregiver;
• generating predicted improvements in the risk scores based on care recommendations, which are selected to reduce the risk scores;
• computing trends in the risk scores to determine additional recommendations;
• reserving care resources based on the risk scores;
• generating mortality, morbidity, and brain pathology indicators based on the risk scores;
• generating risk scores for a caregiver based on the subject's risk scores;
• extracting signals from the sensors including biochemical, GPS, respiratory, cardiac, neurological, motion, augmented reality, and blood pressure sensors;
• analyzing the speech recordings for linguistic biomarkers indicative of neurological health;
• analyzing blood biomarkers associated with neurological diseases;
• analyzing wearable data for symptoms and behaviors indicative of neurological health;
• generating a lifestyle assessment analyzing sleep, exercise, stress, heart health, and diet data;
• producing personalized recommendations based on the neurological and lifestyle assessments.