Abstract: Computer code embedded in an electronic component (e.g., a processor, a sensor, etc.) of a medical device, such as a dialysis machine, can be authenticated by comparing a metadata signature derived from the computer code of the electronic component to a key derived from a pre-authenticated code associated with the electronic component. The metadata signature can be derived by running an error-check/error-correct algorithm (e.g., SHA256) on the computer code of the electronic component. A use of the metadata signature enables detection of any unauthorized changes to the computer code as compared to the pre-authenticated code.

Abstract: A secure artificial intelligence (AI) enabled wearable medical sensor platform is used for adaptive operation according to features and techniques described herein. Operational parameters are modified based on data inputs thereto that provide feedback to the AI systems of the wearable sensor platform. The described technology can facilitate adaptive optimizations provided by AI machine learning algorithms in a manner that can beneficially assist in the monitoring and treatment of a patient. For example, the system described herein may be used for the continuous monitoring of the physiological parameters and health of a patient's vascular access point (for example, the fistula) and may provide, among other things, early warnings of possible infection at the vascular access location.

Abstract: A secure artificial intelligence (AI) enabled wearable medical sensor platform is used for adaptive operation according to features and techniques described herein. Operational parameters are modified based on data inputs thereto that provide feedback to the AI systems of the wearable sensor platform. The described technology can facilitate adaptive optimizations provided by AI machine learning algorithms in a manner that can beneficially assist in the monitoring and treatment of a patient. For example, the system described herein may be used for the continuous monitoring of the physiological parameters and health of a patient's vascular access point (for example, the fistula) and may provide, among other things, early warnings of possible infection at the vascular access location.

Abstract: Computer code embedded in an electronic component (e.g., a processor, a sensor, etc.) of a medical device, such as a dialysis machine, can be authenticated by comparing a metadata signature derived from the computer code of the electronic component to a key derived from a pre-authenticated code associated with the electronic component. The metadata signature can be derived by running an error-check/error-correct algorithm (e.g., SHA256) on the computer code of the electronic component. A use of the metadata signature enables detection of any unauthorized changes to the computer code as compared to the pre-authenticated code.

Abstract: A secure artificial intelligence (AI) enabled wearable medical sensor platform is used for adaptive operation according to features and techniques described herein. Operational parameters are modified based on data inputs thereto that provide feedback to the AI systems of the wearable sensor platform. The described technology can facilitate adaptive optimizations provided by AI machine learning algorithms in a manner that can beneficially assist in the monitoring and treatment of a patient. For example, the system described herein may be used for the continuous monitoring of the physiological parameters and health of a patient's vascular access point (for example, the fistula) and may provide, among other things, early warnings of possible infection at the vascular access location.

Abstract: Computer code embedded in an electronic component (e.g., a processor, a sensor, etc.) of a medical device, such as a dialysis machine, can be authenticated by comparing a metadata signature derived from the computer code of the electronic component to a key derived from a pre-authenticated code associated with the electronic component. The metadata signature can be derived by running an error-check/error-correct algorithm (e.g., SHA256) on the computer code of the electronic component. A use of the metadata signature enables detection of any unauthorized changes to the computer code as compared to the pre-authenticated code.

Abstract: A system for monitoring a vascular access is provided. The system includes a wearable vascular access monitor which can be a sleeve or other protective covering fitted with two or more sensors for obtaining physiological measurements at different locations from the vascular access. The sleeve or other protective covering is also fitted with an ultra-low power processor for relaying the physiological measurements to a patient's mobile phone. The patient's phone can evaluate the physiological measurements to determine a state of the vascular access, and if the physiological measurements fall out of nominal ranges, the patient's phone can alert a clinic, nurse, or physician. The system can be used to monitor fistulas or grafts used for hemodialysis or peritoneal dialysis.

Abstract: Computer code embedded in an electronic component (e.g., a processor, a sensor, etc.) of a medical device, such as a dialysis machine, can be authenticated by comparing a metadata signature derived from the computer code of the electronic component to a key derived from a pre-authenticated code associated with the electronic component. The metadata signature can be derived by running an error-check/error-correct algorithm (e.g., SHA256) on the computer code of the electronic component. A use of the metadata signature enables detection of any unauthorized changes to the computer code as compared to the pre-authenticated code.

Abstract: Computer code embedded in an electronic component (e.g., a processor, a sensor, etc.) of a medical device, such as a dialysis machine, can be authenticated by comparing a metadata signature derived from the computer code of the electronic component to a key derived from a pre-authenticated code associated with the electronic component. The metadata signature can be derived by running an error-check/error-correct algorithm (e.g., SHA256) on the computer code of the electronic component. A use of the metadata signature enables detection of any unauthorized changes to the computer code as compared to the pre-authenticated code.