Motion Platform for HIIDAA Reduction via Biometric Feedback
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Solution Overview
Problem
Current methods lack effective non-pharmacological interventions for managing Hyperactivity-Impulsivity-Irritability-Disinhibition-Agitation (HIIDAA) behaviors in Alzheimer's Disease, Autism Spectrum Disorders, and Behavioral Psychological Symptoms of Dementia, which are challenging to manage and significantly impact quality of life and caregiver burdens.
Innovation Solution
An automated motion platform combining oscillating single-axis or bi-axial motion with real-time biological and behavioral feedback mechanisms, including facial recognition, heart rate monitoring, and noise input, to provide customized repetitive motion therapy for reducing HIIDAA behaviors, utilizing reinforcement learning algorithms to determine optimal feedback mechanisms for agitation reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated feedback mechanisms and multiple sensors are integrated to improve therapy customization, then treatment effectiveness is improved, but device complexity increases
Solution Approach 1:
The system divides the complex monitoring and therapy delivery function into separate modular components: video camera for facial expression monitoring, audio sensor for noise detection, heart rate monitor for physiological tracking, and separate actuators for different motion therapies. Each component performs a specific function and can be independently configured, reducing overall system complexity while maintaining comprehensive monitoring capabilities
Solution Approach 2:
The feedback control system serves multiple functions simultaneously: it monitors facial expressions, analyzes vocalizations, tracks heart rate, determines agitation states, and adjusts therapy parameters. This multi-functional approach consolidates what would otherwise require multiple separate systems into a single integrated platform, improving reliability without proportionally increasing complexity
2Ease of operation
If real-time monitoring and automated adjustments are implemented to reduce caregiver burden, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The system automatically monitors the patient's facial expressions, vocalizations, and heart rate in real-time, and autonomously adjusts therapy parameters without requiring caregiver intervention. The feedback control system continuously analyzes sensor data and modifies actuator commands based on detected agitation states, enabling the device to self-regulate and significantly reducing caregiver burden
Solution Approach 2:
The system implements closed-loop feedback control where sensor outputs from video cameras, audio sensors, and heart rate monitors are continuously fed back to the control system. The controller processes this feedback information and automatically adjusts therapy delivery in real-time, creating an autonomous operation mode that reduces caregiver involvement while managing system complexity through standardized control algorithms
Data Source
AI summary
A motion platform combines oscillating single-axis or bi-axial motion and patient biological and behavioral feedback mechanisms for reducing HIIDAA in people experiencing neurological imparities. The platform is driven by actuators that provide single-axis or bi-axial motion. The platform has a planar upper surface on which a wheelchair, chair or other resting furniture can be positioned. The platform motion is actuated based on facial expression and bodily movement recognition feedback, heart rate feedback, standing and fall detection, and/or manual remote control from a wireless or internet enabled device. Noise feedback may also be provided as an input. The device actuation may include oscillating motion to simulate rocking. Music may also be output to further help manage the reduction of HIIDAA of the individual. Reinforcement and deep learning algorithms also use optimal time-dependent actuation profiles based on real-time inputs and a database of behavior characteristics of the patient.