Responsive whole patient care compression therapy and treatment system

Abstract

Apparatus and methods relate to a pneumatic compression therapy device configured to suggest content to the patient based on a determined disease state, the content pertaining to suggested changes in lifestyle based on a standard of care. In an illustrative embodiment, the suggested changes may include modifications to treatment location, treatment time, diet, eating habits, or sleeping schedule. Various examples may further sample the patient's health and automatically adjust a treatment parameter within a predetermined parameter range based on a history of measured parameters, such as limb volume, for example. In coordination with the therapeutic treatment, the therapy device may deliver suggested content to guide the patient to make more healthful lifestyle choices to reduce recovery time and improve patient health outcomes.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application Ser. No. 62/090,092, titled “Dynamic Active-Compression-Therapy and Treatment System,” filed by Ryan Douglas on Dec. 10, 2014. This application incorporates the entirety of the foregoing document herein by reference.

TECHNICAL FIELD

Various embodiments relate generally to pneumatic compression therapy devices.

BACKGROUND

Compression therapy and/or massage therapy is used in treating various diseases and injuries. Compression therapy may be a non-invasive mechanical method used for a variety of therapies and treatments. Compression therapy may be used to aid in the healing of wounds. Injuries that require portions of the body to be stabilized during recovery may use compression therapy to aid in such stabilization. Compression therapy may be used in the treatment of venous leg ulcers. Various forms of compression therapy may be used to treat different types of Edema, including lymphedema. Lymphedema is a chronic form of Edema that results from inadequate functioning of the lymphatic system, leading to accumulation of lymph fluid. Compression therapy for treatment of Lymphedema may be adjusted according to a patient's disease state. Deep vein thrombosis may involve compression therapy in a treatment regime.

Compression therapy may be performed using active methods and/or passive methods. Passive methods may include the use of compression bandages and compression garments. Compression garments may be garments that have an elastic that provides compression to a location on the body. Tight-fitting leggings may be worn to provide compression of the legs, for example. Tight-fitting sleeves may be worn to provide compression of an arm, for example. Active methods may include the use of pneumatic pumps and inflatable chambers configured to provide pressure to parts of the human body.

SUMMARY

Apparatus and methods relate to a responsive and dynamic pneumatic compression therapy device configured to suggest content to the patient based on a determined disease state, the content pertaining to suggested changes in lifestyle based on a standard of care. In an illustrative embodiment, that suggested changes may include modifications to treatment location, treatment time, diet, eating habits, or sleeping schedule. Various examples may further sample the patient's health and automatically adjust a treatment parameter within a predetermined parameter range based on a history of measured parameters, such as limb volume, for example. In coordination with the therapeutic treatment, the therapy device may deliver suggested content to guide the patient to make more healthful lifestyle choices to reduce recovery time and improve patient health outcomes.

Apparatus and associated methods relate to a compression therapy system that automatically adjusts a treatment parameter within a predetermined parameter range based on a history of measured limb volume. In an illustrative embodiment, ambulatory integration of a pneumatic engine may record a history of measurements of the time to inflate one or more pneumatic chambers under controlled conditions. The time to inflate the one or more pneumatic chambers may be indicative of a limb volume. A historical record indicating increasing time to inflate the one or more pneumatic chambers may indicate a reduced limb volume. In some embodiments, the compression therapy system may advantageously reduce a scheduled therapy time in response to an increasing time-to-inflate measurement.

Various embodiments may achieve one or more advantages. For example, some embodiments may rapidly improve a patient's health outcomes for a specific disease state by combining sensing and treatment of emotional human factors in coordination with corporal compression therapy for that disease state. Some examples may observe and detect likely changes in emotional state for patients who may feel isolated and alone and emotionally burdened by the challenges and setbacks that may occur for chronic conditions, such as lymphedema. Compliance with treatment regimens may be improved and yield substantially improved patient outcomes and reduced recovery time, and may reduce degradation to even more debilitating disease states (e.g., lymphostatic elephantiasis). By serving as a treatment hub for a specific disease state, and by providing lifestyle information to improve patient outcomes around the specific disease state, a therapy system may serve as a whole patient support system, capable of implementing and improving compliance with physician-prescribed therapeutic regimes, combined with healthy lifestyle choices. By monitoring the patient's current disease state and emotional states, the hub may suggest timely and appropriate encouragement, guidance, and healthy lifestyle information. Advantageously, the home based system can readily monitor patient compliance and certain observable lifestyle behaviors to understand how to provide encouragement and corrective action steps early when a variance occurs. In the event a trend changes, the system may reduce the time to report a user's health to a third party, such as a responsible relative, health care provider, or physician. In some embodiments, a user's use of a therapy device may be automatically reported to a physician. Such automatic reporting may facilitate a physician in prescribing a therapy regime. In some embodiments, automatic reporting to and from a hospital may help coordinate patient care. For example, a patient who requires daily compression therapy may be hospitalized for unrelated reasons. The hospital may be automatically informed by a dynamic treatment system of the patients prescribed therapy regime. Such coordination of health information may result in improved patient health.

In some embodiments, the time in which a user must perform therapy may be reduced by active monitoring of health metrics by a dynamic treatment system. For example, the dynamic treatment system may monitor a tissue density, and as the patient's tissue density improves, the dynamic treatment system may automatically reduce the therapy time. Such therapy time reductions may permit the user to participate in more non-therapy activities. Improved emotional health may result from such a time optimizing dynamic system.

The details of various embodiments are set forth in the accompanying drawings and the description below. Other features and advantages will be apparent from the description and drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a schematic of a dynamic treatment system in network communication with interested parties.

FIG. 2 depicts a block diagram of an exemplary compression therapy analysis system.

FIG. 3 depicts a block diagram of an exemplary compression therapy coordination engine.

FIG. 4 depicts a flowchart of an exemplary method of dynamically modifying a treatment program within predetermined limits

FIG. 5 depicts a flowchart of an exemplary method of automatically generating alerts to a physician.

FIG. 6 depicts an exemplary graph plotting a health metric vs. days of treatment.

FIG. 7 depicts an exemplary compression therapy device adjusting Lymphedema treatment parameters according to limb density, determined as a function of the time required to inflate the compression cuff to the treatment pressure.

FIGS. 8A and 8B depict measurement of a patient's arm and leg circumference for limb density calculation in support of Lymphedema therapy.

FIGS. 9A and 9B depict measurement of fluid displacement of a patient's arm and leg for limb density calculation in support of Lymphedema therapy.

FIG. 10 depicts the block diagram of an exemplary bio-impedance measurement system used for Lymphedema therapy.

FIG. 11 depicts the electrode equivalent circuit of an exemplary measurement sensor used for Lymphedema therapy.

FIG. 12 depicts an exemplary method of operating a compression therapy controller module (CTCM) as a system hub configured to deliver personalized compression therapy coupled with interactive delivery of emotional wellness content to treat lymphedema.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

To aid understanding, this document is organized as follows. First, a dynamic adjustment of compression therapy parameters is briefly introduced with reference to FIG. 1. Second, with reference to FIGS. 2-3, exemplary dynamic treatment systems will be described. Then exemplary methods of using treatment related parameters will be described, with reference to FIGS. 4-5. Next, with reference to FIG. 6, a plot of an exemplary health metric will be used to describe adaptive therapy treatment. Next, with reference to FIG. 7, exemplary apparatus and methods for autonomously treating a patient while adjusting treatment as a function of measured disease state is presented. Then, with reference to FIGS. 8-9, methods of measuring limb density for use in Lymphedema treatment are presented. Next, with reference to FIGS. 10-11, the structure of an exemplary bio-impedance measurement apparatus is presented. Finally, with reference to FIG. 12, a method of operating a compression therapy hub configured to deliver personalized compression therapy coupled with interactive delivery of emotional wellness content to treat lymphedema is disclosed.

FIG. 1 depicts a schematic of a dynamic treatment system in network communication with interested parties. In FIG. 1, an exemplary dynamic treatment system 100 is in network communication with a Doctor 105. The Doctor, may submit, for example, prescription for a patient to use an active compression therapy device. Patient A 110 may have an illness or injury in which an active compression therapy device 115 may be used to provide compression of Patient A's leg. The active compression therapy device 115 used by Patient A 110 may log data and send the logged data to the network for use by the dynamic treatment system 100. The dynamic treatment system 100 may be in network communication with a hospital 120 so as to coordinate Patient A's prescribed treatment with the hospital, should Patient A require hospitalization. The manufacture (“MFG”) 125 of the compression therapy device 115 used by Patient A 110 may communicate information (e.g., testing data, upgrade software, etc.) to the dynamic treatment system 100. Various other patients, such as Patient B 130, may use an active compression therapy device 135 that is also sharing use data with the dynamic treatment system 100. The dynamic treatment system 100 may advantageously optimize a recommended therapy routine for Patient A 110 when using compression therapy device 115 based upon the data collected by one or more of the described sources.

FIG. 2 depicts a block diagram of an exemplary compression therapy analysis system. In FIG. 2, a compression therapy analysis system 200 is in communication with a data warehouse 205, a device manufacturer 210, a physician 215 and two active compression therapy devices 220. Each of the active compression therapy devices 220 include a GPS position system 225, a user input/output interface 230 and one or more sensors 235. Each of the active compression therapy devices 220 may log data, when the compression therapy devices 220 are used. For example, when worn by a patient, a compression therapy device 220 may log the location of the user. Such location logging may be used to evaluate whether the patient was sedentary or moving during the compression therapy.

The user input/output interface 230 may provide bidirectional communication between the compression therapy device and the user. The sensors 235 may record parameters associated with the compression therapy device 220 and/or associated with the patient. For example, patient measurements, such as heart rate, blood oxygenation, blood flow, flow of other bodily fluids (e.g. Lymph), tissue health, tissue density, body temperature, etc. may be sensed by the sensors 235. Device related parameters, such as pump pressure, garment pressure, flow rate, inflation time, air temperature, etc. may be measure by the sensors 235.

The physician 215 may communicate prescription information 240 related to one of the patients 220 under the care of the physician 215. The physician 215 may receive and or send data to the compression therapy analysis system via a physician input/output interface 245. For example, a webpage, email and/or smartphone application may be used as a vehicle for communicating information between a physician 215 and a compression therapy analysis system 200.

The manufacturer 210 may share research data 250 and/or testing data 255 with a compression therapy analysis system 200. The manufacturer 210 may have an input/output interface for communicating with the compression therapy analysis system 200. For example, a computer program may facilitate communication between the compression therapy analysis system 200 and the manufacturer 210.

The data warehouse 205 may have a patient database 260, a manufacturer database 265 and/or a physician database 270. These databases may be accessible to the compression therapy
k_ECF=[((K_B²ρ_ECF²)/D_B)^1/3]/100

Measured Quantities:

• • H=Height of the Measured Person (cm)
  • W=Weight of the Measured Person (kg)
  • R_E=Extra-Cellular Resistance (Ω)=R₀

Constant Values:

• • ρ_ECF=Resistivity of Extra-Cellular Fluid (Ω·cm)
  • K_B=4.3
  • D_B=1.05 kg/liter

The electrode material and design may be key parameters that directly affect the measurements. The value of R_E may be determined using regression methods. The corresponding resistance at different frequencies is determined and extrapolation performed to determine the resistance value at zero frequency (R₀). The more frequencies used for the interpolation, the more accurate the interpolation at zero frequency will be. In some embodiments, the number of frequencies used in a multi-frequency bio-impedance measurement may be constrained to the minimum number of frequencies required to obtain an acceptable result in a given application, where the minimum number of frequencies may be obtained by appropriate experimentation in view of the frequency-sensitive properties of the various electrode materials. The table below lists typical values of Rd and Cd for some typical electrode materials, and the corresponding magnitude impedance.

	Material	Rd	Cd	[Rd||Cd] @ 1 kHz
	Wet Ag/AgCl	350 kΩ	25 nF	6 KΩ
	Metal Plate	1.3 MΩ	12 nF	13 kΩ
	Thin Films	550 MΩ	220 pF	724 kΩ
	MEMS	650 kΩ	Negligible	650 kΩ

In various implementations, a circuit for bio-impedance measurement may provide a current at either a fixed frequency or a range of frequencies depending on the selected method. An exemplary bio-impedance measurement circuit may incorporate a filtering process to eliminate noise, which affects the impedance reading, especially at lower frequencies. In some embodiments, a bio-impedance measurement circuit may integrate a method to transfer/communicate information to the user.

In various embodiments, electrodes may be incorporated at the ends of the treatment garments. In some implementations, electrodes may be made from either metallic electrodes (noble metals or stainless steel) or electrolytic gel electrodes (standard ECG electrode).

Further embodiments may be communicatively and operatively coupled with a database to track the progress of patients, output, and potentially share results. A database in some embodiments may involve a website database that the users can log in to, to track the progress of their treatment, or a smartphone application that the data can be shared with, using wireless or Bluetooth technology. In various implementations, further analysis of the data may be performed to determine how that correlates to the length of treatment. Analysis in some implementations may include extensive research and computation on the data to determine the correlation between the progress and the length of treatment, including empirical regression methods performed on the data to determine the relationship.

Various exemplary devices may use the concepts of bio-impedance to determine the volume of lymph fluid present in the body. Some embodiments, may determine the volume of lymph fluid present in the body using algorithms developed with regression methods based on the data received from testing. In other embodiments, a circuit utilizing a microcontroller and waveform generator may provide a voltage and current that may pass through the patient at a set frequency or a range of frequencies. In further embodiments, an exemplary device may determine an output waveform and phase change effective for calculating the impedance using an electric circuit or programming. Exemplary devices may include wireless/Bluetooth capabilities to transfer information to an end user. In various implementations, electrodes may be made of either metals (noble metals or stainless steel) or electrolytic gel. Some embodiments may have a system that logs the progress of treatment based on the volume measurements taken for each user.

In further embodiments, information may be provided to the user via either a website database or a phone application. Various embodiments may suggest customized treatment plans based on the progress of the current treatment plan. Various implementations may be FCC and FDA compliant.

Some embodiments may archive patient response measurements and disease state estimates to provide historical data tracking the patient's response to treatment over time. Various implementations may analyze historical patient response measurement to identify trends. Trends may include disease progression or remission, disease cessation, or variance in patient performance or wellness. Some implementations may incorporate additional data in the analysis of patient progress or disease state, including tracking patient mood using techniques including voice recognition or patient responses to inquiries about the patient's well-being.

Trend analysis may be used in various embodiments to adapt treatment protocols as the patient's disease state improves or worsens. Exemplary devices may increase frequency or duration of treatment, vary pressure, alert a physician, or adapt treatment in other ways as appropriate if a patient's disease state trend is determined to be worsening, or not improving according to reference data. In various embodiments, reference data may include standards of care, such as reference disease state levels. In some implementations, an exemplary device may determine appropriate actions including modifications to treatment or alerts, as a function of disease state and standards of care. For example, in a limb treatment scenario an exemplary device may determine the lymph concentration has increased beyond a standardized range for the patient and the progress expected, and the determination may trigger the activation of a more aggressive treatment.

Some embodiments may provide guidance to the patient, for managing chronic conditions, such as lymphedema, based on analysis of disease state and patient performance trends. Exemplary devices may suggest modifications to patient lifestyle choices directed to improving treatment outcome when trend analysis determines treatment is not progressing as expected. The suggested modifications to lifestyle choices may include changes to treatment location, treatment time, diet, eating habits, or sleeping schedule, determined as a function of disease state trends and standards of care. Additional embodiments may suggest, for example, that a patient may resume activity previously restricted by a physician, when trend analysis determines the patient's condition has improved. Further embodiments may incorporate artificial intelligence techniques to determine appropriate support content that may benefit the patient and help the patient manage and treat a chronic disease. Support content may include instructional content to help the patient with treatment, and psychological support content to help the patient improve their sense of well-being. In various implementations appropriate support content may be determined as a function of the patient's disease state, standards of care, expected prognosis, historical data, or other factors.

In one exemplary aspect, a dynamic treatment apparatus may include an output system adapted to provide system output to interact with the patient and apply a predetermined treatment protocol to the patient, and an input system adapted to receive a system input representative of a patient response and measurement of a treatment outcome responsive to the applied treatment protocol. A controller is operatively coupled to the input system to receive the system input, and operatively coupled to the output system to apply the predetermined treatment protocol to the patient. A memory device is operatively coupled to the controller and containing instructions, that when executed by the controller, cause the controller to perform operations to apply the treatment to a patient and suggest changes to treatment protocols or patient activities as a function of treatment outcome and the patient's disease state. The operations include (i) apply the treatment protocol to the patient, (ii) determine the treatment outcome and the patient's disease state based on the received system input, (iii) suggest changes in lifestyle. In various examples, the suggested changes may include modifications to treatment location, treatment time, diet, eating habits, or sleeping schedule. The modifications may be based on the determined disease state and a predetermined standard of care. The operations to suggest changes may further include interactive delivery of supportive palliative medical, psychological, emotional, or counseling content to a patient based on the determined disease state and the predetermined standard of care. The apparatus also includes a user interface operatively coupled to the controller to interact with the patient regarding the generated suggested changes.

In various embodiments of the apparatus, the operations may include: estimate the patient's disease state based on the received system input, and determine the supportive content as a function of the estimated disease state and the predetermined standards of care; archive and analyze patient responses to queries and measurements of treatment outcome to identify disease state trends; or, receive, at the memory device, information that defines the predetermined standards of care. The user interface may receive, from the controller, display information that, when displayed on a display device, presents to the user at least some of the generated suggested changes.

The operations may further include: determine a personalized profile of a patient as a function of sensor input data or subjective input data; determine suggested changes to the treatment protocol and suggested changes to patient activity as a function of the personalized profile of a patient and prescriptive data; or, determine suggested changes to the treatment protocol and suggested changes to patient activity as a function of the personalized profile of a patient and historical data.

In another exemplary aspect, a treatment method may include providing an output system adapted to provide system output to interact with the patient and apply a predetermined treatment protocol to the patient, providing an input system adapted to receive a system input representative of a patient response and measurement of a treatment outcome responsive to the applied treatment protocol, and providing a controller operatively coupled to the input system to receive the system input, and operatively coupled to the output system to apply the predetermined treatment protocol to the patient. The method may also include providing a memory device operatively coupled to the controller and containing instructions, that when executed by the controller, cause the controller to perform operations to apply the treatment to a patient and suggest changes to treatment protocols or patient activities as a function of treatment outcome and the patient's disease state. The operations may include: (i) apply the treatment protocol to the patient; (ii) determine the treatment outcome and the patient's disease state based on the received system input; and, (iii) suggest changes in lifestyle, the suggested changes comprising modifications to treatment location, treatment time, diet, eating habits, or sleeping schedule, based on the determined disease state and a predetermined standard of care.

In various implementations of the method, the operations to suggest changes may further include interactive delivery of supportive palliative medical, psychological, emotional, or counseling content to a patient based on the determined disease state and the predetermined standard of care.

In another exemplary aspect, a method of operating a compression therapy controller module (CTCM) as a system hub configured to deliver personalized compression therapy coupled with interactive delivery of emotional wellness content to treat a disease state known to benefit from active compression therapy includes several steps. One step is updating a current disease state in the patient based on a first input signal sampled during operation of a compression therapy device, the compression therapy device being adapted to treat the known disease state, the first signal having a predetermined correlation to known effective treatments. Another step is updating a current emotional state of the patient based on a second input signal comprising an indicator having a predetermined correlation with emotional state of a patient with a disease state known to benefit from compression therapy. Another step is, based on the current emotional state of the patient, generating content to deliver to the patient, the generated content comprising information that indicates a behavioral change that the patient can make to improve upon the current disease state or the current emotional state of the patient. Another step is, based on the current emotional state and current disease state of the patient, selecting a therapeutic mode to apply to the patient, the therapeutic mode selection being made between a first mode and a second mode. In the first mode, the controller causes a compression therapy device operably connected to the controller to deliver a compression therapy protocol to physically treat the disease state of the patient. In the second mode, the controller causes the generated content to be delivered to the patient.

In various embodiments of the method, the first input signal may include a pressure signal indicative of a pressure in an inflatable chamber configured to deliver compression therapy to a region of the patient's body. The first input signal may include a measured inflation time of an inflatable chamber configured to deliver compression therapy to a region of the patient's body. The second input signal may include a voice monitoring signal, the method further comprising updating the current emotional state of the patient by analyzing the voice monitoring signal to detect indicia of the emotional state of the patient.

The method may include updating the current disease state of the patient by analyzing the voice monitoring signal to detect indicia having a predetermined correlation to the disease state. The second input signal may include an electronic signature indicia. The electronic signature indicia may include metrics that indicate a variance in the patient's normal electronic communication usage patterns, wherein the variance metrics exceed a predetermined threshold relative to historic electronic communication usage patterns.

The second input signal may include indicia of activity level patterns relative to time of day. The second input signal may include measured sleep patterns, indicia of work activity patterns, measurement of total computer use patterns, patient-reported information about how the patient feels, tracking information indicative of a measure of exercise, tracking information indicative of a measure of movement.

The mode selection comprises selecting both the first mode and the second mode. The method may include programming the controller to repeat the therapeutic mode selection at least once per day. The method may include actuating a compression therapy device operatively coupled to deliver therapy to the patient by inflating and deflating at least one chamber according to a predetermined compression therapy profile. The method may include updating the compression therapy profile for the patient as a function of the first input signal and the second input signal. The generated content may include interactively delivered supportive palliative medical, psychological, emotional, or counseling content to the patient based on a predetermined standard of care for lymphedema. The method may include, at the controller, receiving, from a remote server over a communication network, updates to the predetermined standard of care for lymphedema.

In certain embodiments, a treatment device or system may update treatment protocols based on a known disease state and a sensed patient state. Some embodiments include a device that may use known disease state and patient state to suggest lifestyle activities appropriate to the patient. Furthermore, some implementations may include a device that uses known disease state and patient state to suggest lifestyle activity, or to provide interactions that improve and maintain a patient's mental state of being to help ensure compliance to treatment requirements and lifestyle suggestions. Accordingly various embodiments may be responsive to whole patient care needs, including human factors, and may advantageously reduce health care costs for compression therapy patients, and improve disease state and patient state wellness outcomes.

1. In an illustrative aspect, a method of operating a compression therapy controller module (CTCM) as a system hub configured to deliver personalized compression therapy coupled with automated management of an emotional state of a patient may include delivering emotional wellness content to promote compliance with a prescribed treatment protocol or desired emotional state for treating a disease state that is known to benefit from active compression therapy.

2. The method may include identifying a predetermined target emotional state profile associated with treatment of a current disease state of the patient who has a prescribed treatment protocol that includes receiving therapy from a compression therapy device adapted to treat the disease state.

3. The method may include assessing, with the device, a current emotional state of the patient based on an emotional input signal received by the device. The emotional input signal may include an indicator having a predetermined correlation with the current emotional state of the patient with the disease state.

4. The method may include assessing, with the device, a current physical state of the patient based on a physical input signal received by the device. The physical input signal may include a physical indicator having a predetermined correlation with the current emotional state of the patient with the disease state. The physical input signal may include at least one human factor signal associated with the disease state. The human factor signal may include measurement of limb volume. The human factor signal may include measurement of limb density of the patient.

5. The method may include determining a variance between the target emotional state profile and the assessed current emotional state. The method may include generating, based on the determined variance, a content to deliver to the patient. The generated content may include information that the patient can consume to reduce the variance. The method may include delivering the generated content to the patient.

A number of implementations have been described. Nevertheless, it will be understood that various modification may be made. For example, advantageous results may be achieved if the steps of the disclosed techniques were performed in a different sequence, or if components of the disclosed systems were combined in a different manner, or if the components were supplemented with other components. Accordingly, other implementations are contemplated within the scope of the following claims.

Claims

1. A method of operating a compression therapy controller module (CTCM) as a system hub configured to deliver personalized compression therapy coupled with automated management of an emotional state of a patient by delivering emotional wellness content to promote compliance with a prescribed treatment protocol or desired emotional state for treating a disease state that is known to benefit from active compression therapy, the method comprising:

(a) identifying a predetermined optimal target emotional state profile associated with treatment of a current disease state of the patient who has a prescribed treatment protocol that includes receiving therapy from a compression therapy device adapted to treat the disease state;

(b1) assessing, with the device, a current emotional state of the patient based on an emotional input signal received by the device, the emotional input signal comprising an indicator having a predetermined correlation with the current emotional state of the patient with the disease state;

(b2) assessing, with the device, a current physical state of the patient based on a physical input signal received by the device, the physical input signal comprising (1) a physical indicator having a predetermined correlation with the current emotional state of the patient with the disease state, and (2) at least one human factor signal associated with the disease state, wherein the human factor signal comprises a at least one of: measurement of limb volume or measurement of limb density of the patient;

(c) determining a variance between the optimal target emotional state profile and the assessed current emotional state;

(d) based on the determined variance, generating content to deliver to the patient, the generated content comprising information that the patient can consume to reduce the variance; and,

(e) delivering the generated content to the patient.

2. The method of claim 1, wherein the physical input signal comprises at least one biosense signal associated with the disease state.

3. The method of claim 2, wherein the biosense signal comprises a measurement of at least one vital sign of the patient.

4. The method of claim 1, wherein the human factor signal further comprises a measurement of physical movement of the patient.

5. The method of claim 1, wherein the human factor signal further comprises a voice monitoring signal recording indicia of the patient's voice that have a predetermined correlation with the emotional state of the patient.

6. The method of claim 1, further comprising assessing, with the device, a current lifestyle of the patient based on a lifestyle input signal received by the device, the lifestyle input signal comprising a lifestyle indicator having a predetermined correlation with the current emotional state of the patient with the disease state.

7. The method of claim 6, wherein the lifestyle input signal comprises information about a sleep metric for the patient, wherein the sleep metric is associated with the disease state.

8. The method of claim 6, wherein the lifestyle input signal comprises information about a diet metric for the patient, wherein the diet metric is associated with the disease state.

9. The method of claim 6, wherein the lifestyle input signal comprises information about an exercise metric for the patient, wherein the exercise metric is associated with the disease state.

10. The method of claim 6, wherein the lifestyle input signal comprises information about an electronic signature indicia for the patient, wherein the electronic signature indicia is associated with the disease state.

11. The method of claim 10, wherein the electronic signature indicia comprise metrics that indicate a variance in the patient's normal electronic communication usage patterns, wherein the variance metrics exceed a predetermined threshold relative to historic electronic communication usage patterns of the patient.

12. The method of claim 6, wherein the lifestyle input signal comprises indicia of activity level patterns relative to time of day.

13. The method of claim 1, further comprising: (f) repeating steps (b)-(e) according to a prescribed treatment schedule.

14. The method of claim 1, wherein if the determined variance exceeds a predetermined threshold, the device generates a notification message for transmission to a third party care provider of the patient.

15. The method of claim 1, further comprising receiving, at the device, updated information from a remote server, wherein the device is configured to modify the treatment protocol for the patient based on the updated information.

16. The method of claim 1, further comprising actuating the compression therapy device operatively coupled to deliver therapy to the patient by inflating and deflating at least one chamber in the device according to a predetermined compression therapy profile.

17. The method of claim 1, wherein the disease state comprises lymphedema.