Week of 11/1/22
Here are this week’s patent picks and nutshell descriptions. This week’s categories are Intelligent Sensors, Autonomous Vehicles and Machine Learning.
Intelligent Sensors
There appears to be a lot of activity in the biosensor recently, from sleep apnea monitors to surgical stapling devices.
My Pick:
Microbiota Activity Sensor And Decision Support Tool
DOCUMENT ID
US 11488699 B1
DATE PUBLISHED
2022-11-01
ASSIGNEE INFORMATION
NAME
CERNER INNOVATION, INC.
In a Nutshell: uses smart sensors that receive patient microbiota data and detects changes or trends in the data.
Abstract
An improved decision support tool is provided for detecting, diagnosing, or treating human patient based on detected changes or trends in microbiota-related activity of the patient. The decision support tool determine a longitudinal pattern of relative abundances or diversity levels of microbiota, and subsequently determine the occurrence of alternations or trends, which may indicate or be related to meaningful clinical events, such as a change in condition for the patient. In one embodiment, a joint determination of statistical significance of change and trend is first detected and then utilized to determine an occurrence of clinically meaningful microbiota activity in a patient. The decision support tool may further initiate an intervening action based on a detected change or trend, such as generating an electronic notification, modifying a treatment program, providing a recommendation, automatically allocating health care resources to the patient, or automatically scheduling a consultation with a caregiver.
From detailed description of the drawings:
At a high level, this disclosure describes, among other things, technologies for an improved decision support tool for detecting (and treating human patients based on) changes or trends in microbiota-related activity of the patient. In one example embodiment, a decision support tool determines or receives a longitudinal pattern of relative abundances or diversity levels of microbiota, and automatically analyses this data to detect the occurrence of alternations or trends, which may indicate or be related to meaningful clinical events, such as a change in condition for the patient. The decision support tool may further initiate an action based on a detected change or trend, such as by way of example and without limitation, generating an electronic notification and providing the electronic notification to the patient or caregiver, modifying a treatment program, providing a recommendation, automatically allocating health care resources to the patient, or automatically scheduling a consultation with a caregiver. In some embodiments, the electronic notification may further include statistically robust quantitative interpretations of the patterns or pattern changes. In some embodiments, the decision support tool comprises (or may be embodied as) a smart sensor system that senses or receives serial of microbiota data (or successive measurements of microbiota data) about a human patient and detects the changes or trends. In some embodiments, smart sensor uses the machine learning classification, such as described herein, for detecting or responding to the clinically significant changes or trends.
BACKGROUND
(1) The human body is host to a complex and abundant aggregation of microbes, collectively referred to as the microbiota. Anatomical sites that are the subject of measurements of microbiota include gut, skin, genitals, oropharynx, and respiratory tract. Microbiota in body fluids such as blood, urine, and sputum are also routinely measured. The relevance of such measurements to medical diagnostics and therapeutics is diverse. By way of example, the gut microbiota has physiological functions associated with nutrition, the immune system, and defense of the host. The intestinal microbiota plays a number of important roles in mammalian health, including gut development, extraction of energy from food, protection against pathogens, and development, maturation, and responsiveness of the immune system. Alterations in the composition of the intestinal bacterial communities have been implicated in obesity, inflammatory bowel disease, diabetes, and a variety of disease states. However, to date, the conventional technology and approaches to healthcare decision support have not understood or effectively utilized the range of gut microbiota compositional states during health in efforts to define and characterize prognosis, progression of illness, and treatment effectiveness.
Autonomous Vehicles
Dozens of patents were issued this week in the autonomous vehicle state. Waymo, Apple, Meta and AAA were awarded patents.
My Pick:
Wiper Timing And Geometry To Minimize Sensor Occlusion
DOCUMENT ID
US 11485328 B1
DATE PUBLISHED
ASSIGNEE INFORMATION
NAME
Waymo LLC
In a Nutshell: provides a system of rotating and fixed sensors including a wiper to clear a sensor cover of dirt and debris. It’s interesting the Eric Schmidt, the former CEO of Google, is an inventor on this patent.
Abstract
This technology relates to a system for clearing a sensor cover. The system may be comprised of a first sensor that rotates within a sensor cover, a plurality of second sensors that are fixed relative to the sensor cover, a first wiper that is configured to clear the sensor cover of debris, and a motor. The motor may rotate the first wiper in a first direction at a first predetermined rotation rate defined at least in part by a second predetermined rotation rate of the first sensor.
BACKGROUND
(1) Various types of vehicles, such as cars, trucks, motorcycles, busses, boats, airplanes, helicopters, lawn mowers, recreational vehicles, amusement park vehicles, farm equipment, construction equipment, trams, golf carts, trains, trolleys, etc., may be equipped with various types of sensors in order to detect objects in the vehicle's environment. For example, vehicles, such as autonomous vehicles, may include such LIDAR, radar, sonar, camera, or other such imaging sensors that scan and record data from the vehicle's environment. Sensor data from one or more of these sensors may be used to detect objects and their respective characteristics (position, shape, heading, speed, etc.).
(2) However, these vehicles are often subjected to environmental elements such as rain, snow, dirt, etc., which can cause a buildup of debris and contaminants on these sensors. Typically, the sensors include a cover to protect the internal sensor components of the sensors from the debris and contaminants, but over time, the cover itself may become dirty. As such, the functions of the sensor components may be impeded as signals transmitted and received by the internal sensor components are blocked by the debris and contaminants.
Machine Learning
Active areas this week are health related, shopping, smart sensing and payment methods. Block, Inc, was active with two issued patents.
My pick:
System And Method For Physically Detecting, Identifying, And Diagnosing Medical Electronic Devices Connectable To A Network
DOCUMENT ID
US 11489847 B1
DATE PUBLISHED
2022-11-01
ASSIGNEE INFORMATION
NAME
NOKOMIS, INC.
In a Nutshell: takes electromagnetic emissions from a medical device, conditions the emissions in the frequency domain and determines a signature for the device along with detecting anomalies in the signature, possibly indicating a cyber attack in real time.
A method for detecting, in a real-time manner, a presence or an absence of an anomaly in or a cyber attack onto a medical apparatus comprises the steps of capturing, with an antenna, one or more emissions of electromagnetic energy from the processing devices within medical apparatus; converting, with a receiver coupled to the antenna, the one or more emissions from an analog to a digital form; generating, with a controller, a digital signal in a time domain; converting, the digital signal from the time domain to a frequency domain, the digital signal containing a signature of cross modulation products from the non-linear attachments; processing, in the frequency domain, the signature of cross modulation products to determine mixing characteristics of the cross modulation products; and detecting, based on the mixing characteristics, the absence or the presence of the anomaly or the cyber attack.
BACKGROUND
1. Technical Field
(4) The subject matter relates to protection of electronic devices. The subject matter may relate to protection of medical electronic devices connected to a data bus or network. The subject further matter may relate to medical electronic devices protection from cyber and cyber-physical attacks.
2. Description of Related Art
(5) The following background information may present examples of specific aspects of the prior art (e.g., without limitation, approaches, facts, or common wisdom) that, while expected to be helpful to further educate the reader as to additional aspects of the prior art, is not to be construed as limiting the present subject matter, or any embodiments thereof, to anything stated or implied therein or inferred thereupon.
(6) Complex medical electronic devices can be critical to the safety and wellbeing of medical patients, dispersing medicine, controlling medical records, and diagnosis of complex medical issues. Adversarial intrusion or subversion of medical electronic devices' software and hardware can jeopardize diagnostic assurance, patient lives, and patient privacy and security.
(7) The Food and Drug Administration has provided guidance for manufactures to implement solutions to mitigate cybersecurity risk and risk management. Current solutions to cyber-threats in medical devices can include software solutions that analyze incoming threats, to hardware solutions that isolate data storage to provide a physical barrier to medical records. These approaches cannot adequately answer the cyber threat currently facing the medical device community.
(8) To ensure diagnostic integrity, patient privacy, and medical treatment success, the user, physician or nurse or manufacturer of the medical device can have an immediate need for a capability to verify and ensure the trustworthiness of critical medical electronic devices, embedded software, hardware, stored medical records or information, and methods to mitigate vulnerabilities or threats. Furthermore, the physician or nurse has a need to be able to detect cyber intrusion events.
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