Detecting falls with mmWave radar
Tom Morton
Founder, Archangel
Falls can be critical for older people. Not only do they often lead to serious health complications. They also place a burden on healthcare providers in terms of increased costs.
Whilst traditional fall detection solutions have helped in alerting stakeholders, including loved ones, they frequently fail to address privacy concerns, data security and challenges for the users when it comes to compliance.
There’s now a pioneering solution in the form of mmWave radar technology which send and receive radio waves that sense motion and body position via sensors. Falls can be detected without impacting on an individual’s privacy, unlike cameras which capture visual data.
In addition to privacy concerns, mmWave technology is both accurate and highly sensitive to subtle movements with immediate data analysis differentiating between normal activities and fall scenarios. This allows for early interventions that could mean the difference between serious injury and rapid recovery.
There are also advantages when it comes to reliability. Radar signals are not impacted by obstacles, furniture or lighting. They are a perfect fit for a range of indoor settings including nocturnal and cluttered spaces.
Far more compact and unobtrusive when compared to traditional, bulky plastic telecare devices, mmWave sensors can be simply and easily installed into existing home and wearable tech solutions delivering user comfort and none of the compliance issues associated with the old technologies.
The risk of any data breaches of personally identifiable information is also minimised aligning with privacy regulations.
Ultimately, the data gained can be easily analysed and acted upon in real time using aggregating platforms such as our own AAL (ambient assisted living). The emphasis shifts from reactive to proactive.
Integrating mmWave radar into fall detection represents a game changing shift towards safer, aging-in-place solutions and the ability to unobtrusively monitor and safeguard vulnerable individuals makes it an invaluable tool in home and healthcare automation.
The onward march of technology can present a challenge in terms of future-proofing, particularly with regard to burgeoning AI technologies. However joined up thinking and a collaborative approach involving engineers, healthcare providers and policymakers can mitigate these concerns and lead to continually raised standards of care.
Enhancing the safety of the individual without intruding on privacy is a balance that mmWave radar achieves. By embracing these technologies, we can create safer living environments that uphold personal privacy and improve the quality of life.
The old adage of ‘pride coming before a fall’ may well need rewording. ‘Prediction comes before a fall’ could well prove to be a more accurate phrase.
