Psychiatric Disorders Mood
Conditions
Brief summary
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.
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.
Interventions
DEVICESensor wrist watch
Participants will wear a sensor wrist watch which will collect data
Sponsors
Sheba Medical Center
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Detecting changes in the mental health condition of psychiatric patients | 6 months | 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 |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Detection of illegal drug usage | 6 months | 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 |
Outcome results
None listed