Wearable Cognitive Therapy Device for Real-Time Impulsivity Detection
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Solution Overview
Problem
Current therapies are unable to automatically sense and therapeutically respond to neural signals associated with impulsivity during anticipatory periods, which are critical for intervening in neuropsychiatric disorders.
Innovation Solution
A wearable device using non-invasive scalp and physiological sensors to detect electrophysiological and physiological signals, processing them with a computing device to identify impulsivity states and provide alerts or deliver electrical stimulation to attenuate impulsivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If no available therapy is used, then the device complexity remains low, but the reliability of detecting and responding to impulsivity states is zero
Solution Approach 1:
The system segments the detection task into multiple independent sensor components: scalp electrophysiology sensors for neural signal detection, physiological sensors for heart rate and skin conductance monitoring, and location sensors for spatial tracking. Each sensor type targets specific biomarkers of impulsivity, allowing the system to achieve high reliability through distributed measurement rather than relying on a single complex device
Solution Approach 2:
The patent merges multiple sensor modalities (electrophysiological, physiological, and location data) into a unified wearable system that processes signals through a common computing platform. This integration enables cross-validation of impulsivity detection across different signal types while maintaining manageable device complexity through shared processing architecture
2Speed
If real-time detection of neural signals is implemented, then the responsiveness to impulsivity states improves, but the device complexity and energy consumption increase
Solution Approach 1:
The system performs preliminary signal processing and feature extraction at the sensor level before data transmission to the central computing device. Scalp sensors pre-process electrophysiological signals to identify characteristic frequency patterns, and physiological sensors pre-process heart rate and skin conductance data to detect impulsivity markers. This preliminary action reduces the computational burden during real-time response decisions, thereby lowering overall energy consumption while maintaining fast responsiveness
Solution Approach 2:
The wearable device implements periodic sampling of neural and physiological signals rather than continuous monitoring, adjusting the sampling rate based on detected state changes. During baseline periods, the system uses lower sampling rates to conserve energy, while switching to higher sampling rates when impulsivity indicators are detected, thus maintaining real-time responsiveness without sustained high energy consumption
3Measurement precision
If multiple sensors are used to detect correlates of NAc signals, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The system applies local quality by positioning specific sensors at locations where they can detect particular correlates of nucleus accumbens activity. Scalp sensors are placed at specific electrode positions to target frontal brain regions associated with impulsivity, while physiological sensors are positioned at specific body locations to capture relevant autonomic responses. This localized sensor placement optimizes measurement precision for specific neural correlates without requiring comprehensive coverage of the entire body
Solution Approach 2:
The patent introduces intermediary processing layers that translate raw sensor signals into interpretable biomarkers of impulsivity. The computing device acts as an intermediary that receives signals from multiple sensors, applies algorithmic processing to identify patterns correlated with NAc activity, and outputs diagnostic indicators. This intermediary processing layer consolidates complexity into a centralized system while maintaining high measurement precision through coordinated multi-sensor input
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The device effectively detects and treats impulsivity states by providing timely alerts and therapeutic interventions, improving specificity, sensitivity, and reliability through combined scalp and physiological signal analysis.
Implementation Method 1
a first sensor configured to be worn on a user and a second sensor configured to be worn on the user. The first sensor is a non-invasive sensor configured to detect an electrophysiology signal at the scalp of the user which is a correlate of a user's NAc signal
Implementation Method 2
The second sensor is a non-invasive sensor configured to detect a physiological signal (e.g., heart rate, heart rate variability, etc.) which is a correlate of a user's NAc signal
Implementation Method 3
The computing device also has an impulsivity software application (app) which programs the computing device to process the sensor signals and utilize a detection algorithm to detect an impulsivity state of the user
Implementation Method 4
an electrical stimulation system configured to deliver electrical stimulation directly to the user in response to the impulsivity state detected by the wearable device
Data Source
AI summary
Devices, systems, and methods for a wearable, real-time cognitive behavioral detection and/or therapy device for detecting impulsivity states of a user, and for providing alerts to the patient and/or a patient-identified network of persons, of an impending impulsivity state. The device utilizes a combination of wearable, non-invasive, sensors configured to be worn by a user and to detect electrophysiology signals and/or psychophysiological signals of the user. The sensors output respective sensor signals corresponding to the electrophysiology signals and psychophysiological signals and transmit the respective sensor signals to a computing device. The computing device has a software application which programs the computing device to process the sensor signals and provide informational and/or therapeutic information regarding an impulsivity state of the user. The device may also include a system for delivering electrical stimulation directly to the user in response to the impulsivity state detected by the device.