# US 2022/0036716 A1 · Fall validation with privacy-aware monitoring > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2022/0036716 A1 - Document ID: US20220036716A1 - Status: Published application - Kind: A1 - Application number: 17/390,775 - Filed: 2021-07-30 - Published: 2022-02-03 - Earliest claimed: 2020-08-03 - Assignees: Healthcare Integrated Technologies, Inc. - Applicants: Healthcare Integrated Technologies Inc. - Inventors: Kenneth M. GREENWOOD; Scott Michael BORUFF; Jurgen Klaus VOLLRATH - Web page: https://patentgrep.com/patent/US20220036716A1 ## CPC - G08B 21/043: {detecting an emergency event, e.g. a fall} - A61B 5/1117: {Fall detection} - G06N 3/02: Neural networks - G06T 13/40: of characters, e.g. humans, animals or virtual beings - G08B 21/0469: {Presence detectors to detect unsafe condition, e.g. infrared sensor, microphone (G08B21/0476 takes precedence)} - G08B 21/0476: {Cameras to detect unsafe condition, e.g. video cameras} - A61B 5/0077: {Devices for viewing the surface of the body, e.g. camera, magnifying lens} - A61B 5/165: {Evaluating the state of mind, e.g. depression, anxiety} - G08B 13/19686: {Interfaces masking personal details for privacy, e.g. blurring faces, vehicle license plates} - G08B: SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract A method and system for detecting a person falling, confirming a potential fall, and taking action to mitigate the effects of a fall. ## Claims ### Claim 1 A fall detector, comprising an image capture device, a microphone, and a processor connected to a memory that includes machine-readable code defining an algorithm for controlling the image capture device and microphone to monitor a person for purposes of detecting falls, wherein the image capture device is adapted to capture only select information, and the algorithm is configured to identify flagging events based on falls detected by the image capture device, and to capture sound data from the microphone to supplement information not captured by the image capture device and to corroborate potential falls detected by the image capture device. ### Claim 2 (depends on 1) The fall detector of claim 1, wherein the data not captured by the image capture device includes dead zones not covered by the image capture device, and privacy regions designated in the algorithm as private areas, which are obscured. ### Claim 3 (depends on 1) The fall detector of claim 1, wherein the image capture device includes one or more of a video camera, a camera operating in a frequency range outside the visual spectrum that inherently limits image quality, a digital camera system where the pixel count is kept low enough to limit image quality to protect privacy, and a radar or sonar device. ### Claim 4 (depends on 1) The fall detector of claim 1, wherein the processor is configured to compare verbal and non-verbal input from the microphone to pre-recorded sounds of people falling including exclamations by third parties or by the person being monitored, which are associated with a falling event, in order to corroborate a potential fall detected by the image capture device. ### Claim 5 (depends on 4) The fall detector of claim 4, wherein the algorithm includes an artificial intelligence (AI) system trained on fall image data to identify falls and potential falls. ### Claim 6 (depends on 5) The fall detector of claim 5, wherein the AI system parses the image data captured by the image capture device and identifies trigger events that require corroboration by a second data source, and flagging events that warrant notifying a third-party. ### Claim 7 (depends on 6) The fall detector of claim 6, wherein the second data source comprises sound data from the microphone for the same time frame. ### Claim 8 (depends on 7) The fall detector of claim 7, further comprising a speaker connected to the processor, wherein the algorithm is configured to generate a message to the person being monitored, in the event of a fall or potential fall being detected by the image capture device or microphone. ### Claim 9 (depends on 8) The fall detector of claim 8, wherein the message comprises one or more of: a consoling message in the event of a fall being detected that help is on the way, and a confirmation message in the event of a potential fall to verify that the person did fall, and using the microphone to capture any response for purposes of corroborating data from the image capture device or microphone. ### Claim 10 A fall detector comprising a video camera to capture video data, a processor, and a memory connected to the processor, wherein the memory includes machine-readable code adapted to parse the video data to identify fall events, to obfuscate the video data, and to keep a record of at least one of the video data and the obfuscated video data. ### Claim 11 (depends on 10) The fall detector of claim 10, further comprising a motion detector, wherein the machine-readable code is adapted to keep a record of the video data or obfuscated video data only when motion is detected. ### Claim 12 (depends on 10) The fall detector of claim 10, wherein the machine-readable code is adapted to generate an avatar of each human being captured or recorded by the video camera. ### Claim 13 A method of enhancing the safety of a user in a dwelling, comprising monitoring the user for falls in the dwelling by capturing image and sound data, and corroborating the image data and the sound data in the event of a suspected fall, respectively with sound data and image data captured over a corresponding time frame. ### Claim 14 (depends on 13) The method of claim 13, further comprising corroborating a suspected fall by querying the user about the user's condition.