Technology and dementia diagnosis

Mark Beaumont MD

January 12, 2022



Can your smartphone detect early signs of disease like dementia or diabetes? The answer is possibly.

We live in a digital, internet-based world. Many Americans are using smartphones, tablets, laptops which all provide access to the internet. Research has shown that these mobile devices can capture vital health information that can give clues about overall health including cognitive functioning. This technology is important because changes in our health status can be a sign of a new disease or the worsening of a disease. An additional tool to help inform not only caregivers but also provide healthcare providers with actual data to identify health issues before they become critical can reduce disease progression. Let’s review 2 ways that smartphones can help detect changes in our health condition.

  • Brain function

Researchers are studying applications on smart devices that can detect changes in the way people use their mobile phones and this can possibly give early warnings of dementia. A team from Apple, Eli Lilly, and Evidation Health are working on a system to detect cognitive decline including memory loss based on factors such as slower typing rates and reduced steps taken as measured by a phone’s step counter. In a recent 12-week study of 113 participants, researchers found that they could differentiate between healthy volunteers and those with mild cognitive decline with early-stage Alzheimer’s disease. In addition to this, the application is also being studied regarding its ability to monitor the symptoms of dementia, detect clinical changes in the condition and test the effectiveness of treatments and therapies.

 The University of Oxford is leading a research study called GameChanger where they have developed an app called Mezurio that gets downloaded to smartphones and people play fun, free brain games for five minutes each day over a month. The data is used to diagnose the early stages of dementia a condition with changes to memory and thinking that can be difficult to detect with current clinical tests.   

  • Monitoring of chronic diseases

Applications on smart devices are being adapted to help track vital signs which include our body temperature, blood pressure, pulse, and breathing rate. These devices can also track heart rhythms, monitor blood sugar levels and sleep activity. The ability to monitor and check one’s blood pressure and blood sugar throughout the day provides valuable information. If the blood pressure is consistently high, maybe the patient is not taking the prescribed medication or maybe they are but not according to the recommended schedule. If the values are too low, maybe it is the team to cut the dosage of the medication. These same principles go for treating diabetes with insulin and oral drugs. Some individuals have been diagnosed with irregular heart rhythms. Smartphones can detect these abnormalities and in real-time alert patients and providers of the need for intervention. Smartphone technology can also be used in the detection and monitoring of sleep activity in those diagnosed with sleep apnea. In this condition individuals periodically stop breathing while they are sleeping at night and are unaware of the number of episodes. This condition can lead to fatigue, heart disease, and other conditions.

This research is not meant to replace our current healthcare system as we know it but to improve it. The data from these devices are meant to help with diagnosing and treating patients while reducing inefficiencies and waste. Smart devices provide real numbers based on facts in patients away from the hospital whereas without it reporting providers must rely on subjective reporting from patients which may not always be unbiased.

  1. Lampros C. Kourtis et al. npj Digital Medicine. volume 2, Article number: 9 (2019).
  2. Chen R, Jankovic et al. Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multi-Modal Sensor Treams. In the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19), August 4-8, 2019, Anchorage, AK, USA. ACM, New York, NY, USA.