A computer program has recently been designed that may be able to one day help depression patients monitor their depression symptoms via their smartphones. The technology was developed in Australia and takes advantage of facial recognition and voice recognition technologies.

The program was created by researchers at the Black Dog Institute, a treatment organization for mood disorder patients, and the researchers say that the program has helped them in a lot of ways to figure out what facial symptoms and voice symptoms can be attributed to a person suffering from depression.

The indicators of depression include slowed speech, lack of eye contact, and lack of facial movement. These symptoms appear regularly in depression patients and do not seem to change when looked at from the perspective of the patient’s history and the patient’s background. The symptoms when looked at in combination with the frequency of occurrence could help to determine the severity of the symptoms that the person is suffering from and help healthcare professionals to obtain the appropriate treatments for the patient faster. It will also help the healthcare professional to come up with a plan for ongoing treatment especially in the instances of severe cases of depression.

Diagnosis and monitoring depression symptoms in patients has traditionally been difficult because of the fact that depression patients have a hard time putting their symptoms into words. Currently healthcare professionals rely on interviewing techniques and questionnaires to get this information since it is very difficult to assess what a patient would otherwise behave like normally or after receiving medication or therapies that seem to be improving the symptoms especially if the healthcare professional has only been treating the patient for a short period of time. In addition it is also difficult to compare the severity of the responses of a patient to other patients in their implications for the depression patient’s behavior.

Depression patients also have limited opportunities to get assistance when not visiting their healthcare professional since they can obviously not be treated in an emergency healthcare situation so the researchers have marked this application as a way to help get patients faster treatment without having them do a whole lot to explain how they are feeling.

According to Professor Gordon Parker, who was one of the researchers on the project said that the clinical trials which have been done initially gave a result of an accuracy of about 90 percent which is far greater than current methods at only 65 percent.

The technology has not yet been made available to the public yet due to the fact that the clinical trials are ongoing but the researchers say that there will be more updates soon.

Also The Black Dog Institute researchers will be continuing working the program in order to help develop a working prototype that can be released to healthcare professionals at a later date. There is no word yet on the timeline for rolling out these items as the research is still being done. In addition, the prototype will also need to undergo additional clinical trials.

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