# US 12,599,313 B2 · Health trackers for autonomous targeting of tissue sampling sites > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,599,313 B2 - Document ID: US12599313B2 - Status: Granted - Kind: B2 - Application number: 17/848,154 - Filed: 2022-06-23 - Published: 2023-12-28 - Granted: 2026-04-14 - Earliest claimed: 2022-06-23 - Applicants: ViBo Health LLC - Inventors: Gil Travish - Web page: https://patentgrep.com/patent/US12599313B2 ## CPC - A61B 5/055: involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging - A61B 5/064: {using markers (A61B5/062 takes precedence)} - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract Health trackers for targeting tissue sampling sites in accordance with embodiments of the invention are provided. In one embodiment, a health tracker includes: a scanner for capturing spectral data, the scanner comprising: a magnet configured to generate a field gradient across a region of interest; an RF transmitting antenna configured to generate a localized field; and an RF sensing antenna configured to sense a localized area; and where the scanner is configured to obtain magnetic resonance spectral data from predetermined locations with a volume of interest. ## Claims ### Claim 1 A health tracker for autonomously targeting optimal tissue sampling sites of a user's hand, the health tracker comprising: a scanner for capturing magnetic resonance spectral data, the scanner comprising: an entrance funnel for receiving the user's hand and a hand rest for positioning the user's hand; a magnet configured to generate a magnetic field gradient across a region of interest of the user's hand; an RF transmitting antenna configured to generate a localized field; and an RF sensing antenna configured to sense a localized area; and wherein the scanner is configured to capture the magnetic resonance spectral data from optimal tissue sampling sites within the region of interest of the user's hand; and wherein the health tracker is configured to autonomously determine the optimal tissue sampling sites of the user's hand by: determining a search volume within the region of interest of the user's hand; segmenting the search volume into a plurality of R-regions to narrow the search volume, wherein the plurality of R-regions comprises a first R-region and a second R-region; targeting a plurality of voxels within the first R-region, wherein the plurality of voxels of the first R-region comprises a first voxel within the first R-region and a second voxel within the first R-region; obtaining magnetic resonance spectral data for the first voxel within the first R-region; obtaining magnetic resonance spectral data for the second voxel within the first R-region; and determining the optimal tissue sampling sites using the magnetic resonance spectra data for first and second voxels within the first R-region. ### Claim 2 (depends on 1) The health tracker of claim 1, wherein the health tracker is further configured to autonomously determine the optimal tissue sampling sites of the user's hand by: detecting a first tissue type using the magnetic resonance spectra data for the first voxel within the first R-region and the magnetic resonance spectra data for the second voxel within the first R-region; determining a tissue gradient between the first voxel within the first R-region and the second voxel within the first R-region; and determining a location of the first tissue type using triangulation. ### Claim 3 (depends on 2) The health tracker of claim 2, wherein the scanner captures the magnetic resonance spectral data using nuclear magnetic resonance within the plurality of R-regions. ### Claim 4 (depends on 2) The health tracker of claim 2 further comprising a position sensor and wherein the health tracker is further configured to autonomously determine the optimal tissue sampling sites of the user's hand using the position sensor. ### Claim 5 (depends on 4) The health tracker of claim 4, wherein the health tracker is further configured to assess that the user's hand is in a correct configuration using the position sensor. ### Claim 6 (depends on 5) The health tracker of claim 5, wherein the health tracker is further configured to relay correction information from the position sensor to the scanner, wherein the correction information is used to instruct the user to adjust placement of the user's hand. ### Claim 7 (depends on 2) The health tracker of claim 2, wherein the determining the location of the first tissue type using triangulation includes: assigning a first centroid to the first voxel within the first R-region and a second centroid to the second voxel within the first R-region; determining spectral strengths for the first tissue type at the first voxel within the first R-region and for the second voxel within the first R-region; determining when the spectral strengths of first voxel within the first R-region and the second voxel within the first R-region both have an assigned spectral strength value for the first tissue type; and when determined that the spectral strengths of the first voxel within the first R-region and the second voxel within the first R-region both have the assigned spectral strength value for the first tissue type, determining a triangulated centroid by calculating the tissue gradient between the first and second centroids, wherein the triangulated centroid indicates a relative location of the first tissue type across the first R-region. ### Claim 8 (depends on 2) The health tracker of claim 2, wherein the health tracker is further configured to autonomously determine the optimal tissue sampling sites of the user's hand by: detecting a second tissue type using the magnetic resonance spectra data for the first voxel within the first R-region and the magnetic resonance spectra data for the second voxel within the first R-region; and determining a second tissue gradient between the first voxel within the first R-region and the second voxel within the first R-region; and determining a location of the second tissue type using triangulation. ### Claim 9 (depends on 8) The health tracker of claim 8, wherein the health tracker is further configured to obtain a tissue gradient for each tissue type detected in the plurality of R-regions. ### Claim 10 (depends on 8) The health tracker of claim 8, wherein the determining the location of the second tissue type using triangulation includes: assigning a first centroid to the first voxel within the first R-region and a second centroid to the second voxel within the first R-region; determining spectral strengths for the second tissue type at the first voxel within the first R-region and for the second voxel within the first R-region; determining when the spectral strengths of first voxel within the first R-region and the second voxel within the first R-region both have an assigned spectral strength value for the second tissue type; and when determined that the spectral strengths of the first voxel within the first R-region and the second voxel within the first R-region both have the assigned spectral strength value for the second tissue type, determining a triangulated centroid by calculating the tissue gradient between the first and second centroids, wherein the triangulated centroid indicates a relative location of the second tissue type across the first R-region. ### Claim 11 (depends on 1) The health tracker of claim 1, wherein the health tracker is further configured to autonomously determine the optimal tissue sampling sites of the user's hand by: targeting a plurality of voxels within the second R-region, wherein the plurality of voxels of the second R-region comprises a first voxel within the second R-region and a second voxel within the second R-region; obtaining magnetic resonance spectral data for the first voxel within the second R-region; obtaining magnetic resonance spectral data for the second voxel within the second R-region; and determining the optimal tissue sampling sites using the magnetic resonance spectra data for first and second voxels within the second R-region. ### Claim 12 (depends on 1) The health tracker of claim 1, wherein the RF transmitting antenna is configured to generate the localized field using RF steering. ### Claim 13 (depends on 12) The health tracker of claim 12, wherein the scanner is configured to obtain the magnetic resonance spectral data from the optimal tissue sampling sites within the region of interest of the user's hand by using the magnetic field gradient across the region of interest generated by the magnet and the localized field generated by the RF transmitting antenna using RF steering. ### Claim 14 (depends on 13) The health tracker of claim 13, wherein the use of the magnetic field gradient and the RF steering reduces complications related to noise from adjacent regions.