Opsis healthcare grade emotion AI helps healthcare professionals deal more effectively with depression, mental illness and remote patient monitoring

Mental Health is a complex systemic disorder with many nonmotor symptoms which include neuropsychiatric features such as cognitive impairment and psychosis dominate that have been challenging to be recognised by healthcare providers. Depression is a condition that is extremely hard to monitor even if someone is in a treatment program. The gap between people needing care and those who receive effective treatment remains substantial due to lack of affordability and trained personnels.

 

Opsis emotion AI technology is of healthcare grade. Our technology helps healthcare professionals deal more effectively with depression and mental illness. It measures facial expressions, speech, gestures & context to analyse a person’s emotional state precisely, with finer granularity, capturing subtle facial cues and small variations in affective states. It helps detect mental health conditions such as depression, anxiety, stress and suicidal tendencies. We also identify non-motor Stage 1 and Stage 2 symptoms for Depression, Anxiety, Cognitive decline, Psychosis, Sleep problems and Hallucinations. The underlining purpose is to detect early signs for medical conditions like Dementia and Alzheimer’s Disease. 

Emotions and health are closely interrelated. Doctors can also use our emotion analytics to help identify a deterioration in chronic illnesses such as diabetes, cancer and heart disease in patients. Depression, stress and anxiety tend to worsen these conditions as they down-regulate various parts of the cellular immune response.

 

In mental health screening, our technology can help enable staffs to perform accurate screenings for government sectors such as public health, defense or for companies such as mining, shipping where good mental health is critical to help protect staffs against accidents. 

 

Our solution can also be used in monitoring, recognizing, and evaluating emotions for various medical purposes, such as remote patient monitoring in hospitals and home nursing care. We use emotion sensing (depression) combined with pain detection to monitor progress for stroke, acute pain and incisive care recoveries. Pain detection from facial expressions is highly reliable using a set of facial muscle-based action units. Automation of 24/7 remote patient monitoring can help support nurses in taking care of seriously ill patients. It also enables hospitals to allocate manpower resources more efficiently, helps to lower the cost of service while maintaining high quality care for patients.

Mental Health Treatment

  • Detect non-motor Stage 1 and Stage 2 symptoms for Depression, Anxiety, Cognitive decline, Psychosis, Sleep problems and Hallucinations
  • Detect early signs for medical conditions like Dementia and Alzheimer’s Disease
  • Particularly useful in virtual counselling, which is much less expensive than in-person consultative processes with psychologists or therapists. This is especially important due to the long duration of care needed to coach mental wellness. 
  • Help in long-term mental or behavioural therapy

Mental health screening

  • Can access accurately the emotional state of mind of patient
  • With just 15-20 minutes of the assessment, the social worker is able to tell what protocol to implement – whether to send the patient to counsellor, clinical or specialist for care planning
  • Time taken to detect mental health issues is reduced from 1 hour to 15 minutes
  • Reduce social worker’s experience requirement from 3 to 5 years to just 3 weeks
  • Help enable staffs to perform accurate screenings for government sectors such as public health, defense or for companies such as mining, shipping where good mental health is critical to help protect staffs against accidents

Remote Patient Monitoring

  • Evaluate patients’ emotional state of mind, such as depression, as well as pain conditions identified through facial cues
  • Monitor progress for stroke, acute pain and incisive care recoveries
  • Predict potential alarm with psychometric analytics – if the algorithm detects that the patient may be suicidal or feeling extreme pain, it will prompt alerts to the caregiver for fast intervention
  • Help to connect and fill information gaps between consultations  
  • Help support nurses in taking care of seriously ill patients, facilitates optimal manpower resource allocation for the hospital
  • Lower cost of service while maintaining high quality care for patients
  • To support home caregiver in nursing care – particularly useful in cases where the care recipients are suffering from depression, anxiety, Alzheimer’s, chronic illnesses like cancer, or recovering from stroke and post-surgery.

Remote Consultation

  • Integrate emotion recognition technology into existing tele-health platforms in hospitals
  • Detect patient’s emotional state to alert doctors to the need for further examination 
  • Help detect a deterioration of chronic illnesses such as diabetes, cancer and heart disease in patients
  • Help in risk profiling of patients so doctors can prioritize their time to attend to more severe cases
  • Emotion analytics can be integrated with more patient database and sharing models for developing more medical service modalities to monitor and predict health state of patients.