System and methods for remotely monitoring lean muscle mass
Systems and methods for lean muscle mass monitoring of patients and for identifying and treating at least one of Cachexia or Sarcopenia are disclosed. The system may include a dynamometer provided to patients, the dynamometer being configured to perform remote monitoring. The dynamometer may be used and data may be collected by patients without the supervision of a healthcare professional. Using the collected data, lean muscle mass may be tracked over time, to provide fast and accurate assessment of conditions. Using such an assessment, early treatment options can be targeted to patients to avoid progression into various disease states, for examples, more severe states of at least one of Cachexia or Sarcopenia.
1. A system for improving analysis of lean muscle mass or lean body mass, the system comprising:
a health service platform, including at least a first cloud based resource; and
a dynamometer configured to determine hand grip strength measurements, the dynamometer including a communication transceiver configured to pair with a mobile device or the health service platform, wherein the dynamometer is configured to:
remotely capture the hand grip strength measurements for a patient according to a system defined frequency; and
communicate the hand grip strength measurements to the mobile device or the health service platform;
wherein at least one of the mobile device and the health service platform, including at least the first cloud based resource is configured to:
receive the hand grip strength measurements;
fit the hand grip strength measurements to a respective diagnostic model that best fits a state of the patient;
responsive to fitting the hand grip strength measurements to the respective diagnostic model:
provide an indication regarding the state of the patient by:
using a comparison model to compare with the respective diagnostic model representative of the state of the patient, and based on the comparison:
identify the state of the patient by categorically classifying the state of the patient into at least one of: Sarcopenia, Cachexia, or pre-Cachexia and generate the indication comprising one of: improving, worsening, or same state within the identified state of the patient;
based on the identified state and generated indication for the patient, update the system defined frequency at which the dynamometer is to be used by the patient for subsequent measurements of hand grip strength and
determine a diagnosis for the patient, wherein the determination comprises:
building a time based model of muscle of the patient using a historical set of the hand grip strength measurements captured remotely by the dynamometer; and
determining the diagnosis for the patient based on the identified state, the generated indication, and a grip strength change amount over time obtained from the time based model of muscle of the patient; and
responsive to the determination of the diagnosis, trigger administration of a treatment of at least one of: pre-Cachexia, Cachexia or Sarcopenia to the patient.
2. The system of claim 1 , wherein the system is further configured to, based on the worsening state of the patient, determine a first interventional action to be presented to the patient.
3. The system of claim 2 , wherein the system is further configured to present the first interventional action to the patient.
4. The system of claim 3 , wherein the system is further configured to, after presenting the first interventional action to the patient, based on persistence of the worsening state of the patient, determine an escalated second interventional action.
5. The system of claim 3 , wherein the system is configured to determine the first interventional action without user input.
6. The system of claim 1 , wherein the health service platform automatically changes the system defined frequency responsive to determining a new state of the patient.
7. The system of claim 1 , wherein the health service platform fits the hand grip strength measurements taken over time to the respective diagnostic model of patient state and a potential treatment option.
8. The system of claim 7 , wherein the system displays the potential treatment option to a healthcare professional.
9. A method of analyzing lean muscle mass or lean body mass, the method comprising:
remotely capturing hand grip strength measurements for a patient according to a system defined frequency using a dynamometer including a communication transceiver configured to pair with a mobile device or health service platform;
communicating the hand grip strength measurements by the dynamometer to the mobile device or the health service platform;
fitting the hand grip strength measurements to a respective diagnostic model that best fits a state of the patient using a at least one of the mobile device and the health service platform including at least a first cloud based resource;
responsive to fitting the hand grip strength measurements to the respective diagnostic model:
providing an indication, by at least one of the mobile device and the health service platform, regarding the state of the patient by:
using a comparison model, by at least one of the mobile device and the health service platform, to compare with the respective diagnostic model representative of the state of the patient, and based on the comparison:
identifying, by at least one of the mobile device and the health service platform, the state of the patient by categorically classifying the state of the patient into at least one of: Sarcopenia, Cachexia, or pre-Cachexia and generating, by at least one of the mobile device and the health service platform, the indication comprising at least one of: improving, worsening, or same state within the identified state of the patient;
based on the identified state and generated indication for the patient, updating, by at least one of the mobile device and the health service platform, the system defined frequency at which the dynamometer is to be used by the patient for subsequent measurements of hand grip strength;
determining, by the health service platform, a diagnosis for the patient, comprising:
building a time based model of muscle of the patient using a historical set of the hand grip strength measurements captured remotely by the dynamometer; and
determining the diagnosis for the patient based on the identified state, the generated indication, and a grip strength change amount over time obtained from the time based model of muscle of the patient; and
responsive to the determination, triggering administration of a treatment of at least one of: pre-Cachexia, Cachexia or Sarcopenia to the patient.
10. The method of claim 9 , further comprising, based on the worsening state of the patient, determining a first interventional action to be presented to the patient.
11. The method of claim 10 , further comprising presenting the first interventional action to the patient.
12. The method of claim 11 , further comprising, after presenting the first interventional action to the patient, based on persistence of the worsening state of the patient, determining an escalated second interventional action.
13. The method of claim 11 , further comprising determining the first interventional action without user input.
14. The method of claim 9 , further comprising automatically changing the system defined frequency responsive to determining a new state of the patient.