The rapidly increasing rate of the ageing population has led to a higher rate in people suffering from neurodegenerative diseases. Neurodegenerative diseases, such as Alzheimer’s and Parkinson’s disease, are characterised by the progressive loss of brain cells, which leads to a decline in a person’s cognitive abilities, and eventually leads to death. The alarming increase in people suffering from these diseases has created a global socioeconomic burden that affects caregivers, nurses, and family members, just as much as the patient themselves. Due to the critical nature of these diseases, it is paramount that systems and devices can detect and monitor neurodegenerative diseases as early as possible, so that the right treatment can be provided to hinder its progression. Existing technologies have provided key results in the detection and monitoring of neurodegenerative diseases. However, they are limited by their bulky size, high costs, and inconvenient or invasive approach.
Meanwhile, microwave sensing technology has generated promising results in several medical applications, such as cancer and stroke detection. The ability to fabricate components easily and integrate them into a wearable prototype makes microwave sensing a promising non-invasive, cost-effective, and portable or wearable solution for medical diagnostics. This work proposes the use of microwave sensing as an inexpensive, non-invasive, reliable, accurate, efficient, and wearable tool for monitoring the progression of neurodegenerative diseases. For evaluation, models were created to emulate symptoms of Alzheimer’s disease to demonstrate the technology. It is observed that microwave sensing was able to detect brain atrophy and lateral ventricle enlargement with a minimum change of 5%. In addition, microwave sensing could non-invasively detect and image regions of the brain affected by Alzheimer’s disease pathology, providing a transformational and major improvement compared to PET scans that rely on biomarkers. Moreover, microwave sensing could detect Alzheimer’s disease at one of its earliest stages: mild cognitive impairment. This work provides a promising and transformative approach for wearable and non-invasive neurodegenerative disease monitoring
