Abstract: Computer code embedded in an electronic component 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.

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: Constraining adaptive optimizations of a state of an operation module of a medical device includes determining if a new state has at least one operational parameter that is outside a constraint that has been provided to the medical device in a non-repudiable manner, accepting the new state if no operational parameters are outside any of the constraints, and reverting the medical device to a previous valid state if at least one operational parameter is outside at least one of the constraints. The adaptive optimizations may be provided using artificial intelligence along with relevant inputs thereto. The medical device may be a dialysis system. Constraint data may be provided to the medical device along with a one-way hash value of the constraint data using, for example, a SHA 256 hash. The one-way hash value may be digitally signed using a private key that is part of a public/private key pair.

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: 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.

Abstract: Constraining adaptive optimizations of a state of an operation module of a medical device includes determining if a new state has at least one operational parameter that is outside a constraint that has been provided to the medical device in a non-repudiable manner, accepting the new state if no operational parameters are outside any of the constraints, and reverting the medical device to a previous valid state if at least one operational parameter is outside at least one of the constraints. The adaptive optimizations may be provided using artificial intelligence along with relevant inputs thereto. The medical device may be a dialysis system. Constraint data may be provided to the medical device along with a one-way hash value of the constraint data using, for example, a SHA 256 hash. The one-way hash value may be digitally signed using a private key that is part of a public/private key pair.

Abstract: Constraining adaptive optimizations of a state of an operation module of a medical device includes determining if a new state has at least one operational parameter that is outside a constraint that has been provided to the medical device in a non-repudiable manner, accepting the new state if no operational parameters are outside any of the constraints, and reverting the medical device to a previous valid state if at least one operational parameter is outside at least one of the constraints. The adaptive optimizations may be provided using artificial intelligence along with relevant inputs thereto. The medical device may be a dialysis system. Constraint data may be provided to the medical device along with a one-way hash value of the constraint data using, for example, a SHA 256 hash. The one-way hash value may be digitally signed using a private key that is part of a public/private key pair.

Abstract: Constraining adaptive optimizations of a state of an operation module of a medical device includes determining if a new state has at least one operational parameter that is outside a constraint that has been provided to the medical device in a non-repudiable manner, accepting the new state if no operational parameters are outside any of the constraints, and reverting the medical device to a previous valid state if at least one operational parameter is outside at least one of the constraints. The adaptive optimizations may be provided using artificial intelligence along with relevant inputs thereto. The medical device may be a dialysis system. Constraint data may be provided to the medical device along with a one-way hash value of the constraint data using, for example, a SHA 256 hash. The one-way hash value may be digitally signed using a private key that is part of a public/private key pair.