The Engineer – Radar sensor could predict Alzheimer’s and fall accidents


Researchers in Sweden have developed a radar sensor to predict fall accidents and cognitive illnesses such as Alzheimer’s disease.

The team, at Chalmers University of Technology, said its radar sensor can read a person’s walking pattern and can be attached to furniture, walls and ceilings in the home and in healthcare settings.

“Our method is both precise and easy to use. It can help healthcare staff to carry out a more reliable risk analysis and tailor interventions to achieve a significant effect early on. Hopefully it can help to solve a growing challenge for society,” said Xuezhi Zeng, a researcher in biomedical electromagnetics at Chalmers University of Technology.

Fall accidents and cognitive illnesses such as Alzheimer’s disease are increasing as the population ages. Preventive measures can reduce both suffering and costs.

In Sweden, around 100,000 people aged 65 or over have such bad falls each year that they require medical care, with 70,000 of them needing to be admitted to hospital. Approximately 1,000 elderly people die each year due to fall accidents. In the USA it is estimated that three million elderly people seek care in an emergency department due to fall accidents each year.

The Chalmers team’s new method uses a small radar sensor to acquire real-time, high-resolution reading of a person’s walking pattern, especially the time required to take a step.

“It is the variation in step times that is the key. A healthy person normally has a regular gait. But a person at risk of fall accidents often has a large variation in step times. For example, the first step may take a second whereas the second may take two seconds,” Zeng said.


According to the team, a product containing the sensor is no larger than a fire alarm and could be used within the healthcare system, in the home or in care environments for the elderly to identify risks.

Preventive measures such as physiotherapy, tailored training or the adaptation of furnishing in the home can be implemented to prevent fall accidents, avoiding suffering and costly hospital care.

Alongside ease of use, another advantage of the method is that it collects data without filming, meaning it can be used without invasion of privacy, Zeng added.

Alzheimer’s disease is one of the most common causes of dementia, and it is difficult to detect at an early stage. Researchers believe this method could be beneficial in making an early diagnosis, and contribute to preventive measures and an improved quality of life.

The method is based on an off-the shelf radar sensor, therefore a commercial development is feasible in the near future.

In the short term, Zeng hopes that it can be used by the elderly at home and provide healthcare staff with objective and valuable decision support data. She also hopes that in the future the method can facilitate clinical research in the elderly and establish more connections between a change in gait and the development of other illnesses.


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