Thank you for sharing. I can access the paper (perks of working...

Thank you for sharing. I can access the paper (perks of working at uni).
It references BRN twice:
- S. Dey, A. Mukherjee, G. Bzard, and D. McLelland, “Demo:
Human gesture recognition using spiking input on akida neuromorphic platform,” Neural Information Processing Systems
(NeurIPS), 2019.
- “Human gesture recognition using spiking input on akida neuromorphic platform,” https://ir.brainchipinc.com/press-releases/
detail/90/brainchip-and-tata-consultancy-services-tcs-jointly,
BrainChip Inc., and Tata Consultancy Services, 2019.

"Abstract—In the past two decades, radar-based human sensing
has become a topic of intense research. Unlike vision-based
techniques which require the use of camera, radars are unobtrusive
and privacy preserving in nature. Further, radars are agnostic
of the lighting conditions and can be used for through-the-wall
imaging thereby making them hugely effective in many situations.
Compact, affordable radars have been designed that can be
easily integrated with remote monitoring systems. However, the
classical machine learning techniques currently used for learning
and inferring human actions from radar images are compute
intensive, and require large volume of training data, making them
unsuitable for deployment on the network edge. In this paper,
we propose to use the concepts of neuromorphic computing and
Spiking Neural Networks (SNN) to learn human actions from
data captured by the radar. To the best our knowledge, this is
the first attempt of using SNNs on micro-Doppler data from
radars. Our SNN model is capable of learning spatial as well
as temporal features from the data and our experiments have
resulted in 85% accuracy which is comparable with the classical
machine learning approaches that are typically used on similar
data. Further, the use of neuromorphic and SNN concepts make
our model deployable over evolving neuromorphic edge devices
thereby making the entire approach more efficient in terms of
data, computation and energy consumption."

Happy to email the paper to those interested.