Technology & Science

TapRoot combines a personalized behavioral approach with Al technology

Behavioral intervention helps caregivers prevent and mitigate adverse behaviors

Dr. Linda Buscemi has been developing behavioral interventions for over 15 years. Her success is rooted in the belief that adverse behaviors (refusing meals, resisting showers, hitting) stem from unmet needs. TapRoot’s proposal is to personalize treatment, which for many years was only possible for one patient at a time. Today, with the help of AI technology, this method can be widely disseminated, reducing costs and reaching millions of patients with the same personalized approach.

90%

of patients present adverse behaviors

Adverse behaviors diminish patients’ quality of life

These behavioral episodes are the key drivers of caregiver burden

Benefits of behavioral interventions

Fewer adverse behaviors
Reduction in psychotropic medications
Less sedation = decrease in fall risk
Fewer hospitalizations

Adverse Behavior
Jane became aggressive when changing her clothes.

Patient Profile & Context
She broke her shoulder as a teenager.

Behavioral Intervention
Use only button up clothes.

Results
Complications prevented.

AI-Powered

Artificial Intelligence (AI) is filling an existing data gap between observed behavior, intervention, and outcome in the cognitive disorders space.

TapRoot’s AI engine analyzes patients’ multiple data points to better match them with the correct intervention. We are using AI and machine learning to provide extensible, scalable, and augmented capacity for caregivers to support individuals with cognitive impairments, beginning with Alzheimer’s and Dementia patients.

The development of the TapRoot system is expected to support caregivers with a smartphone-based system that provides person-centered behavioral interventions for patients. For identified adverse behaviors such as “resisting showers” or “physical aggression,” a library of behavioral interventions developed by an expert clinical therapist is preloaded into the system. Patient profiles and the effectiveness of the intervention , are used to train the system on the most optimal intervention for specific patients.

Real-time delivery of optimal suggested interventions to a smartphone-based app to speed execution and delivery.

Curated list of a library of interventions per adverse behavior, prepared by an expert clinical therapist.

Fully integrated training and patient management system to facilitate additional caregiver training and support efficient management of patients between different caregivers at shift changes.

Machine learning centered around a neural network predictor for behavioral interventions—tailored to specific patients— that evolve over time.

Patent Pending Filed Application: # 63/000,625 System and Method for Generating Curated Interventions in Response to Patient Behavior.

HIPAA compliant We protect sensitive patient data information. We have physical, network, and process security measures in place and follow them to ensure HIPAA Compliance.

Scalable and accessible Ella is a cloud-based platform and our mobile app version operates on IOS and Android.

“Alzheimer’s is a triple threat unlike any other disease — with soaring prevalence, lack of effective treatment and enormous costs.”

Alzheimer's Association

Until a cure is found caregivers need tools to manage patients. TapRoot’s non-pharmaceutical approaches can help. Here some reference studies that explain how behavioral interventions deescalate adverse behaviors:

“An individualised, non-pharmacological treatment strategy associated with an improvement in neuropsychiatric symptoms in a man with dementia living at home.” Carter, M. M. L., Wei, A. & Li, X. BMJ Case Rep. 12, 229048 (2019).

“Nonpharmacological interventions to reduce behavioral and psychological symptoms of dementia: A systematic review.” Oliveira, A. M. De et al. Biomed Res. Int. 2015, 218980 (2015).

“Evidence-Based Non Pharmacological Practices to Address Behavioral and Psychological Symptoms of Dementia.” Scales, K, Zimmerman, S. & Miller, S.J. Gerontologist, Vol. 58, No. S1, S88–S102 doi:10.1093/geront/gnx167 (2018).