Science, Technology, Engineering, and Mathematics (STEM)-based Feedback Control for Treatment of Mental Illness
- Feedback control system perspective
- Sensors for biosignals: EEG, ECG/HRV, etc.
- Actuators; Light, sound (e.g., music), smell, etc.
- Computer algorithms, on-line machine learning, adaptation, and feedback control for individual/group personalization and robustness
Process and Controller (each by itself):
- Modeling (e.g., ODEs, stochastic models)
Basic System (process and controller) Properties:
- Real-time/frequency domain properties/constraints
Specifications (closed-loop properties, "design objectives"):
- Stability, tracking
- Disturbance rejection
- Construct the controller to generate inputs to the process so that the goals are met.
- Can construct a controller if it is implemented in technology, but at times use the feedback control system to model a feedback loop in the human body (e.g., an interconnected neurosystem).
- For technology, the process of control design results in a control algorithm that can be implemented (e.g., via a virtual reality system or in Matab by gathering biosignals and generating inputs such as music or video).
- Control algorithm implemented in a computer is a brain prosthetic.
Intelligent Control: For a more comprehensive treatment of control design methodology, with or without a mathematical model and one that is connected to biological and technological systems, see the book Biomimicry for Optimization, Control, and Automation.
Cooperation: Network-based views of social supports for a patient, or neural processes leading to emergent pattern/behavior, often benefit from a distributed and networked view that incorporates cooperation. For work on an several relevant distributed cooperation strategies, see the overview, experiments in our Distributed Dynamical Systems Laboratory, along with publications, books, and directions.