Various implementations of the invention relate to a
silicon-embedded multi- spectral
lidar system and method for non-invasive, remote monitoring of
pathological conditions of an individual. The
system integrates multiple
laser sources, photodetectors, and a
processing module onto a
silicon chip, enabling the capture and analysis of spatial, spectral, scattering and temporal data from a target subject (e.g., individual). By utilizing
lidar signals at various wavelengths, various implementations of the invention detect three-dimensional ("3D") surface and subsurface features such as micro-movements, vascular patterns, pigmentation changes, and tissue differences and / or irregularities.
Machine learning algorithms process this information from the
lidar to identify and classify abnormalities, enabling applications such as
heart rate and
respiration monitoring,
eye movement tracking for neurological and
mental health assessment, and detection of
pathological skin conditions like
cancer. Various implementations of the invention operate in real-time, adapt to environmental conditions, and support
dynamic monitoring over time, thereby providing a comprehensive, non-contact solution for diagnostics and telemedicine, for example. Various implementations of the invention may comprise a compact
silicon chip form factor suitable for portable and / or hand-held, scalable health monitoring applications across diverse environments.