Retail Store Kiosks: blood pressure, vision, cognitive, body mass index
Smart Phones: stress levels, ECG, blood oxygen levels, pulse, blood pressure
Fit Bit: pulse, exercise levels, sleep cycles, sleep metrics
OUR ALGORITHM + BEHAVIOR CHANGE = ALZHEIMER’S SOLUTION
Having an effective algorithm isn’t enough if its recommendations aren’t
followed – that is, if physiological change doesn’t occur. The idea of a “person’s therapy team” describes the people who read, evaluate, and act upon the algorithm’s directions. A person’s therapy team might consist of one person only: a person interested in taking steps to improve their cognitive health or to prevent future dementia-related diseases. This person might themselves have no disease and no symptoms of disease. That person’s personal physician might be further included in their team, as blood tests are administered to gain further insight.
In contrast, for a person with advanced Alzheimer’s disease, that person’s therapy team might include themselves, multiple physicians and specialists, multiple caregivers, multiple family members, therapists, nurses, physician’s assistants, and the person’s wider social network.
The outputs of the computer system cater to the expectations and capabilities of the many potential members of the person’s therapy team. Output can be in different spoken languages, at different grade levels, at different levels of medical expertise, and at different levels of confidentiality. Alzheimer’s AI-Expert System’s initial output can be read and written by electronic health record (EHR) systems. Upon this compact format are built illustrative descriptions and graphics targeted for the appropriate audiences, such as PDF files, Web sites, and mobile apps.
Inputs about a person’s medical state come from many sources: electronic health records, printed lab results, personal verbal reports, full genome sequences, raw brain scan images, Web site questionnaires, sensor-based mobile devices (such as fitness trackers and electronic scales), social network interactions, and mobile applications. Software development efforts surrounding these inputs continues incessantly as their capabilities and pervasiveness expand – and the imagination of soft-ware designers encompasses ever more ways to track behavior and motivate its change.
Inputs into the system also come from the scientific and human communities related to this field. New drugs, interactions, dosages, off-label uses, side effects, allergies, and combinations emerge daily. Information on the biological mechanisms related to the disease continues to improve and grow in richness. Documentation of user experiences across the connected world is growing exponentially. Most important are increased understanding of what works and what doesn’t in the psychology of motivation: what causes effective behavior changes – what sticks and what doesn’t.