The app is the brainchild of Dr Mark Matthews, a former English teacher turned computer scientist who specialises in human-computer interactions. Named MoodRhythm, the app is based on the idea that the body‘s natural rhythms, known as circadian rhythms, are a major influence on human wellbeing, especially in patients with bipolar disorder, a mental condition  characterised by extreme mood swings, from manic highs to depressive lows. Supported by a Marie Curie International Outgoing Fellowship grant, Dr Matthews has been developing the app at Cornell University in the United States in collaboration with leading authorities in this specialist field, Dr Ellen Frank and Professor Geri Gay.

Designed to be used either as part of treatment with a therapist or as a standalone app, MoodRhythm uses a simple diary to help people keep track of their moods and energy levels, but the main focus of Dr Matthews’ research, in collaboration with Dr Tanzeem Choudhury, is the app’s use of smartphone sensors to automatically track daily routines and reduce the need to rely on patients to record behaviour patterns themselves. “This is very important because people with bipolar disorder are more susceptible to stress events in their lives or changes in their routine,” explains Dr Matthews. “These can lead directly to changes in people’s biological rhythms, which in turn can lead to a depressive or a manic episode,” he says.

One key area the app focuses on is sleep habits. A range of different sensors, including the smartphone’s microphone and light sensor, provide a picture of the user’s sleep environment. For patients with bipolar disorder, factors such as whether they sleep with the TV or the lights on can affect sleep quality. But the app does more than this. It also applies a specially designed formula, or ‘algorithm’, which can detect with great accuracy how long the user actually sleeps for - based on activity and noise levels picked up by the phone, including breathing patterns. 

“Another aspect we are looking at is the amount of activity,” says Dr Matthews, “using a gyroscope and accelerometer on the phone as well as network or GPS information.” Previous studies have shown that patients’ level of physical activity will vary in accordance with their wellbeing. If they are becoming manic, for example, a lot more movement and changes of location are expected.

Dr Matthews is also excited by the potential to monitor virtual as well as real-world activity. “The manic phases of bipolar disorder are associated with what is called the ‘flight of ideas’,” he says. “We want to see if we can detect that through low-level interactions with the smartphone such as how often the user is unlocking it, or switching between applications.”

One of the key strengths of MoodRhythm is the fact that it uses an open IT architecture – meaning that the code is available for other programmers to use and that the app itself can be incorporated directly into other health-related initiatives. In recognition of its potential benefits, MoodRhythm was the winner of the Heritage Open mHealth Challenge in the United States for 2013, an award specifically designed to encourage the development of shared platforms for mobile health initiatives.

“Eventually,” says Dr Matthews, “MoodRhythm could benefit the treatment of other illnesses where circadian rhythms have an important bearing, including schizophrenia and even cancer. But for now the focus is on completing the first validation studies relating to bipolar disorder.”

“Once we have the validation studies, the technology is expected to be easily rolled out,” concludes Dr Matthews.