Systems and methods for assessing the health status of a patient
Embodiments herein include medical systems, devices, and methods for assessing the health status of a patient. In an embodiment, a method includes evaluating the presence of volatile organic compounds in a breath or gas sample of the patient with a plurality of graphene sensors to generate volatile organic compound data, wherein the plurality of graphene sensors include sensors that are specific for different volatile organic compounds. The method can further include collecting data regarding the patient's sympathetic nervous activity. The method can further include combining the volatile organic compound data with the collected data regarding the patient's sympathetic nervous activity to form a combined data set. The method can further include matching the combined data set against one or more data patterns to find the best match, the best match indicating the health status of the patient. Other embodiments are also included herein.
1. A method of assessing the health status of a patient comprising:
evaluating the presence of volatile organic compounds in a breath or gas sample of the patient with a plurality of graphene sensors to generate volatile organic compound data, wherein the plurality of graphene sensors include sensors that are specific for different volatile organic compounds;
collecting data regarding the patient's sympathetic nervous activity, the data comprising at least one of heart rate variability (HRV), electrodermal activity (EDA), respiratory sinus arrhythmia (RSA), and baroreceptor sensitivity (BRS);
combining the volatile organic compound data with the collected data regarding the patient's sympathetic nervous activity to form a combined data set; and
matching the combined data set against one or more previously determined data patterns using a pattern matching algorithm to determine the data pattern that is the best match, wherein the specific previously determined data pattern that is the best match indicates the health status of the patient.
2. The method of claim 1 , wherein the one or more previously determined data patterns are created using a machine learning process.
3. The method of claim 1 , further comprising collecting data regarding the patient's functional status, the data comprising gait data; and
adding the data regarding the patient's functional status to the combined data set.
4. The method of claim 1 , further comprising
collecting data regarding the patient's demographic features; and
adding the data regarding the patient's demographic features to the combined data set.
5. The method of claim 1 , wherein collecting the data regarding the patient's sympathetic nervous activity is performed in a non-clinical setting and evaluating the presence of the volatile organic compounds is performed in a clinical setting.
6. The method of claim 1 , wherein collecting the data regarding the patient's sympathetic nervous activity is performed with a wearable device.
7. The method of claim 1 , wherein collecting the data regarding the patient's sympathetic nervous activity is performed over a time period of at least about 1 day.
8. The method of claim 1 , wherein collecting the data regarding the patient's sympathetic nervous activity is performed with an implanted device.
9. The method of claim 1 , wherein the volatile organic compound data from the breath or gas sample of the patient is downloaded from an external breath sensing system onto at least one of a wearable device and an implantable device.
10. The method of claim 1 , wherein the collected data regarding the patient's sympathetic nervous activity is uploaded from a wearable device to a clinical diagnostic device.
11. The method of claim 1 , wherein one or more of the plurality of graphene sensors are chosen as controls on the collected data regarding the patient's sympathetic nervous activity.
12. The method of claim 11 , wherein the controls correlate with sympathetic nervous activity.
13. The method of claim 12 , further comprising generating a notification if the measured values of the controls do not match the measured values of sympathetic nervous activity.
14. The method of claim 1 , wherein the collected data regarding the patient's sympathetic nervous activity reflects a baseline level of sympathetic nervous activity and changes over the baseline level of sympathetic nervous activity.
15. The method of claim 1 , wherein the plurality of graphene sensors can detect the presence of at least 10 different volatile organic compounds.
16. A diagnostic health system comprising:
a communications circuit;
a memory circuit; and
a processor in electronic communication with the communication circuit and the memory circuit, the processor is configured to
combine volatile organic compound data with collected data regarding a patient's sympathetic nervous activity to form a combined data set, the collected data comprising at least one of heart rate variability (HRV), electrodermal activity (EDA), respiratory sinus arrhythmia (RSA), and baroreceptor sensitivity (BRS); and
match the combined data set against one or more previously determined data patterns using a pattern matching algorithm to determine a pattern that is the best match, wherein the specific previously determined pattern that is the best match indicates the health status of the patient; and
report the health status of the patient based on the best pattern match.
17. The diagnostic health system of claim 16 , wherein the diagnostic health system is a wearable device and the volatile organic compound data is downloaded onto the wearable device from another device.
18. The diagnostic health system of claim 16 , wherein the diagnostic health system is disposed in a clinical environment and collected data regarding a patient's sympathetic nervous activity is uploaded to the diagnostic health system from a wearable device.
19. A diagnostic health system comprising:
a patient-specific device selected from the group consisting of a wearable device and an implanted device; and
an external breath sensing system; and
a processor receiving data from the patient-specific device and the external breath sensing system;
wherein the patient-specific device collects data regarding a patient's sympathetic nervous activity, the data comprising at least one of heart rate variability (HRV), electrodermal activity (EDA), respiratory sinus arrhythmia (RSA), and baroreceptor sensitivity (BRS);
wherein the external breath sensing system collects data regarding the presence of volatile organic compounds in a breath or gas sample of the patient; and
wherein the processor is configured to
combine the volatile organic compound data with the patient's sympathetic nervous activity data to form a combined data set; and
match the combined data set against one or more previously determined data patterns using a pattern matching algorithm to determine a pattern that is the best match, wherein the specific previously determined pattern that is the best match indicates the health status of the patient; and
report the health status of the patient based on the best pattern match.