The Analysis of Physical, Physiological and Behavioral Data Collected From Sensors That Track the Mental Condition of Psychiatric Patients

The Analysis of Physical Physiological and Behavioral Data Collected From Sensors That Track the Mental Condition of Psychiatric Patients Who Are at Risk for Relapse and Who do Not Abide With Their Medication Treatment

An observational study that uses a digital system to collect physiological, physical and behavioral data using worn sensors on psychiatric patients suffering from schizophrenia, bipolar and schizoaffective disorders. The system will enable to analyze the data using a personal digital algorithm in order to detect changes in mental condition and or changes in adherence to medication treatment, and assist in identification of illegal drug usage.

Study Overview

• Status: Unknown
• Conditions: Psychiatric Disorders Mood
• Intervention / Treatment: Device: Sensor wrist watch

Detailed Description

An observational study that uses a digital system to collect physiological, physical and behavioral data using worn sensors on psychiatric patients suffering from schizophrenia, bipolar and schizoaffective disorders. It is a known fact that patients suffering from these disorders are more prone to changes in their mental health condition. Sometimes this change is due to change in medical treatment(whether it was the doctor's decision or low adherence to medication treatment).The mental health condition influences physiological, physical and behavioral aspects which could be detected through the personal digital algorithm and could prevent psychiatric deterioration. For example, in a case of a person in a manic episode investigators would expect to find changes in the personal digital algorithm in physiological aspects(increased heart rate, elevated Heart Rate Variability), physical aspects such as increased number of steps per day, and behavioral aspects(increased hours spent outside of home, excessive activity). An early detection can help in the prevention of psychiatric deterioration in this case and help minimize the suffering caused to the patient and caregivers and perhaps assist in minimizing the need for hospitalization.

The data will be collected using wrist watches. The sensors will collect the physiological data(Heart Rate Variability), physical data(number of steps per day) and the behavioral data(quality of sleep). This data will then be collected and analyzed through big data analysis.

• Study Type: Observational
• Enrollment (Anticipated): 30

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 75 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Adults ,18-75, who are currently hosipatlized in the psychiatric unit at Sheba Medical Center.

Description

Inclusion Criteria:

• Psychiatric patients diagnosed with schizophrenia, bipolar, or schizoaffective disorder according to the DSM 5
• PANSS and CGI scores are 4 and above
• Participants must have the ability to informed consent
• Own a smartphone android 2.3 or IOS 2010 and above

Exclusion Criteria:

• Violent or suicidal participant
• Terminal illness
• Dialysis treatment
• Participants who have a legal guardian
• Participants who do not own a personal smartphone

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Retrospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Detecting changes in the mental health condition of psychiatric patients	The wrist watch using sensors will collect physiological data(Heart Rate Variability), physical data (Steps per day) and behavioral data(Quality of sleep).The algorithm that exists in the watch analyzes the amount of steps, the sleep quality- total sleep versus movement and restful sleep, and the distance travelled.The data collected from the wrist watch will then be transferred to an app located on the participant's smartphone which will enable the investigators to collect and analyze the data using big data analysis.After collecting the data above,the investigators will look for a correlation between changes in the personal digital algorithm and changes in the mental health condition of psychiatric patients	6 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Detection of illegal drug usage	Illegal drug usage can contribute to changes in the personal digital algorithm due to changes in physiological(Heart rate Variability) and physical data(Quality of Sleep) collected from the sensors of the wrist watch and analyzed through big data analysis. Early detection can help in minimizing deterioration of the mental health condition	6 months

Collaborators and Investigators

• Sponsor: Sheba Medical Center

Study record dates

Study Major Dates

• Study Start (Anticipated): October 1, 2018
• Primary Completion (Anticipated): April 1, 2019
• Study Completion (Anticipated): June 1, 2019

Study Registration Dates

• First Submitted: October 8, 2018
• First Submitted That Met QC Criteria: October 19, 2018
• First Posted (Actual): October 22, 2018

Study Record Updates

• Last Update Posted (Actual): October 24, 2018
• Last Update Submitted That Met QC Criteria: October 22, 2018
• Last Verified: October 1, 2018

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Behavioral Symptoms; Problem Behavior; Mental Disorders; Mood Disorders
• Other Study ID Numbers: Sheba-17-4754-AC-CTIL

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No