System and methods for measuring body kinetics for movement disorders and correlating with cognitive and self-assessments

Abstract

A system for measuring body kinetics for movement disorders comprises a primary data processing unit including a sensor unit configured to measure body kinetics and one or more satellite sensor units configured to measure body kinetics and communicatively connected to the primary data processing unit. A related method comprises providing a movement assessment including a disorder correlation value, comparing the disorder correlation value to a threshold value, sending body kinetics data to an assessment application when the disorder correlation value exceeds the threshold value, displaying a cognitive assessment application including cognitive assessment questions based on the disorder type, displaying a self- assessment application including self-assessment questions, constructing an event history combining the cognitive assessment, self-assessment and movement assessment, and quantifying a trend of the cognitive assessment, self-assessment and movement assessment to determine and predict therapeutic efficiency.

Description

SYSTEM AND METHODS FOR MEASURING BODY KINETICS FOR MOVEMENT DISORDERS AND CORRELATING WITH COGNITIVE AND SELF-ASSESSMENTSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. provisional application No. 63 / 583,318 filed on September 18, 2023, incorporated herein by reference in its entirety.BACKGROUND OF THE INVENTION

[0002] Movement disorders are neurological conditions that can cause problems with movement such as increased movement which is voluntary or involuntary, or decreased or slow voluntary movement. There are many possible movement disorders stemming from many possible causes. Example movement disorders include Ataxia, Dystonia, Huntington's disease, Parkinson's disease, Tourette syndrome, and tremors. Example causes of movement disorders include genetics, infections, medicines, nervous system damage, metabolic disorders, stroke, vascular disease, and toxins.

[0003] Treatments are varied for each disorder. In many cases, there is no cure and thus treatments are utilized to improve symptoms. An important part in the management of motor complications is optimizing the patient's medication scheme, which consists of the choice of medications, expected treatment response, and duration of action. Various technologies have been used to monitor movement disorder episodes in an attempt to improve treatment. However, current technologies have seen very limited adoption because of high cost, poor usability, and complexity of interpreting results. These solutions lack important corresponding information on a patient's cognitive state at the time of the movement disorder episode.

[0004] A key driver of clinical decision-making by the provider is not only the presence or absence of motor symptoms measured objectively with the technology but how disabling or bothersome those issues are to the patient. Current technologies lack the ability toprovide / collect these patient reported outcomes to better understand the symptom impact on the activities of daily living and optimize therapy accordingly .

[0005] Caregivers play a crucial role in the patient's daily care and management. However, no current solution aggregates and automatically correlates the patient and caregiver reported outcomes to fill in the gaps in medical history prior to a doctor consultation.

[0006] Thus, there is a need in the art for improved systems and methods of not only measuring body kinetics for movement disorders, but also correlating the objective motor function data to the subjective patient & caregiver reported outcomes, which is key to better treatment outcomes in the movement disorders practice.SUMMARY OF THE INVENTION

[0007] Some embodiments of the invention disclosed herein are set forth below, and any combination of these embodiments (or portions thereof) may be made to define another embodiment.

[0008] In one aspect, a system for measuring body kinetics for movement disorders comprises a primary data processing unit including a sensor unit, configured to be attached to a first location on a body, further configured to measure body kinetics, and one or more satellite sensor units, configured to be attached to one or more additional locations on a body, further configured to measure body kinetics, and communicatively connected to the primary data processing unit, wherein body kinetics calculations are performed locally on the primary data processing unit

[0009] In one embodiment, the one or more satellite sensor units comprises at least one of a waist wearable device, a wrist wearable device, and a heel pad device, and wherein the primary data processing unit comprises a waist wearable device and / or a wrist wearable device.

[0010] In one embodiment, the sensor unit of the primary data processing unit and the one or more satellite sensor units each comprise a microcontroller, a battery, a data storage unit, a transceiver, and an inertial measurement unit.

[0011] In one embodiment, the inertial measurement unit comprises a gyroscope and an accelerometer.

[0012] In one embodiment, the primary data processing unit is communicatively connected to an assessment application on a computing system.

[0013] In one embodiment, the primary data processing unit is wirelessly connected to the computing system via a Bluetooth, a Bluetooth Low Energy (BLE), a Zigbee, a Near-Field Communication (NFC), an infrared, a Wi-Fi, or a cellular network connection.

[0014] In one embodiment, the computing system comprises a processor and a non- transitory computer-readable medium with instructions stored thereon, which when executed by the processor, perform steps comprising receiving a movement assessment including a disorder correlation value from the primary data processing unit, comparing the disorder correlation value to a threshold value, sending body kinetics data to an assessment application when the disorder correlation value exceeds the threshold value, displaying a cognitive assessment application including cognitive assessment questions based on the disorder type, displaying a motor assessment application including relevant motor assessments based on the disorder type, displaying a self-assessment application including self-assessment questions, constructing an event history combining the cognitive assessment, self-assessment and movement assessment, and quantifying a trend of the cognitive assessment, self-assessment and movement assessment to determine and predict therapeutic efficiency.

[0015] In one embodiment, the computing system comprises a desktop computing device, a mobile computing device, a laptop, a tablet, a smartphone, a smart watch, a wrist wearable, a thin client computing device, or a wearable computing device.

[0016] In one embodiment, the computing system comprises a profile for the caregiver, allowing secure linking of the patient profile to the caregiver profile for shared data access, toenable the caregiver to report symptoms and / or take assessments on behalf of the patient, indicate a medication was taken, get notified when triggers are detected by the device and receive medication and assessment reminders.

[0017] In one embodiment, the one or more satellite sensor units are wirelessly connected to the primary data processing unit via a Bluetooth, a Bluetooth Low Energy (BLE), a Zigbee, a Near-Field Communication (NFC), an infrared, a Wi-Fi, or a cellular network connection.

[0018] In one embodiment, the primary data processing unit comprises a processor and a non-transitory computer-readable medium with instructions stored thereon, which when executed by the processor, perform steps comprising collecting six orthogonal satellite data sets on the one or more satellite sensor units, receiving on the primary data processing unit the satellite data sets from the one or more satellite sensor units, collecting six orthogonal data sets on the sensor unit of the primary data processing unit, calculating a 3-dimensional linear movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of each of the one or more satellite sensor units, calculating a 3-dimensional rotational movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units, combining the calculated trajectories into a present kinetic state or a future kinetic state, assigning the kinetic states to a corresponding body part, comparing a correlation of the kinetic states with known movement disorders, and identifying an event corresponding to a movement disorder when the correlation is above a threshold value.

[0019] In another aspect, a method for measuring body kinetics for movement disorders comprises, providing the system as described above, collecting six orthogonal satellite data sets on the one or more satellite sensor units, receiving on the primary data processing unit the satellite data sets from the one or more satellite sensor units, collecting six orthogonal data sets on the sensor unit of the primary data processing unit, calculating a 3-dimensional linear movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units,calculating a 3-dimensional rotational movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units, combining the calculated trajectories into a present kinetic state or a future kinetic state, assigning the kinetic states to a corresponding body part, comparing a correlation of the kinetic states with known movement disorders, and identifying an event corresponding to a movement disorder when the correlation is above a threshold value.

[0020] In one embodiment, the step of receiving on the primary data processing unit the satellite data sets from the one or more satellite sensor units is done in real time.

[0021] In one embodiment, the step of receiving on the primary data processing unit the satellite data sets from the one or more satellite sensor units is done wirelessly.

[0022] In one embodiment, the steps of calculating a linear movement trajectory, calculating a rotational movement trajectory, combining the trajectories into kinetic states, assigning the kinetic states to a corresponding body part, comparing a correlation, and identifying an event corresponding to a movement disorder are performed locally on the primary data processing unit.

[0023] In one embodiment, the corresponding body part comprises a wrist, a waist, or a foot.

[0024] In one embodiment, the known movement disorder is associated with Parkinson's disease and comprises freezing of the gait, resting tremor, bradykinesia, dyskinesia, or slowness of movement.

[0025] In another aspect, a method for correlating body kinetics with cognitive and selfassessments for movement disorders comprises providing a movement assessment including a disorder correlation value, comparing the disorder correlation value to a threshold value, sending body kinetics data to an assessment application when the disorder correlation value exceeds the threshold value, displaying a cognitive assessment application including cognitive assessment questions based on the disorder type, displaying a motor assessment applicationincluding relevant motor assessments based on the disorder type, displaying a self-assessment application including self-assessment questions, constructing an event history combining the cognitive assessment, self-assessment and movement assessment, and quantifying a trend of the cognitive assessment, self-assessment and movement assessment to determine and predict therapeutic efficiency.

[0026] In one embodiment, the computing system comprises a medication management workflow that provides medication reminders based on the configured medication profile and provides both the patient & / or the caregiver an interface to record their daily medication intake to track the medication compliance.

[0027] In one embodiment, the method comprises tracking medication compliance based on the configured medication profile and daily medication intake inputs collected from the patient and / or caregiver profile.

[0028] In one embodiment, the method further comprises sending a report of the event history and trend to a physician for review.

[0029] In one embodiment, the method further comprises sending a report of the event history and trends and / or insights to the caregiver and / or the patient.

[0030] In one embodiment, the method further comprises calculating a new dosing recommendation or physical therapy plan based on the determined and predicted therapeutic efficiency.

[0031] In one embodiment, the step of providing a movement assessment including a disorder correlation value comprises providing a system for measuring body kinetics for movement disorders comprising a primary data processing unit including a sensor unit configured to measure body kinetics, and one or more satellite sensor units, configured to attached to a body part to measure body kinetics, communicatively connected to the primary data processing unit, collecting six orthogonal satellite data sets on the one or more satellite sensor units, receiving on the primary data processing unit the satellite data sets from the one or more satellite sensor units, collecting six orthogonal data sets on the sensor unit of theprimary data processing unit, calculating a 3-dimensional linear movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units, calculating a 3- dimensional rotational movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units, combining the calculated trajectories into a present kinetic state or a future kinetic state, assigning the kinetic states to a corresponding body part, comparing a correlation of the kinetic states with known movement disorders, and identifying an event corresponding to a movement disorder when the correlation is above a threshold value.

[0032] In another aspect, a method for correlating body kinetics with cognitive, selfassessments, and caregiver assessments for movement disorders, comprises providing a movement assessment including a disorder correlation value, comparing the disorder correlation value to a threshold value, sending body kinetics data to an assessment application when the disorder correlation value exceeds the threshold value, displaying a cognitive assessment application including cognitive assessment questions based on the disorder type, displaying a motor assessment application including relevant motor assessments based on the disorder type, displaying a self-assessment application including self-assessment questions, displaying a caregiver assessment application including caregiver assessment questions, constructing an event history combining the cognitive assessment, self-assessment, caregiver assessment, and movement assessment, and quantifying a trend of the cognitive assessment, self-assessment, caregiver assessment, and movement assessment to determine and predict therapeutic efficiency.BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The foregoing purposes and features, as well as other purposes and features, will become apparent with reference to the description and accompanying figures below, which are included to provide an understanding of the invention and constitute a part of the specification, in which like numerals represent like elements, and in which:

[0034] FIG. 1 is a block diagram depicting an exemplary system for measuring body kinetics for movement disorders in accordance with some embodiments.

[0035] FIG. 2 is a block diagram depicting an exemplary sensor device of the system of FIG. 1 in accordance with some embodiments.

[0036] FIGs. 3A-3E show exemplary wearable sensor devices in accordance with some embodiments. FIG. 3A shows exemplary waist wearable devices. FIG. 3B shows exemplary heel pads. FIG. 3C shows exemplary wrist wearables. FIG. 3D shows another embodiment of the exemplary wrist wearable. FIG. 3E shows an exemplary embodiment of the system including a wrist wearable and computing system.

[0037] FIG. 4 is a flow chart depicting an exemplary method for measuring body kinetics for movement disorders in accordance with some embodiments.

[0038] FIG. 5 is a flow chart depicting an exemplary method for correlating body kinetics with cognitive and self-assessments for movement disorders in accordance with some embodiments.

[0039] FIG. 6 is a block diagram depicting an exemplary computing environment in accordance with some embodiments.DETAILED DESCRIPTION OF THE INVENTION

[0040] It is to be understood that the figures and descriptions of the present invention have been simplified to illustrate elements that are relevant for a clearer comprehension of the present invention, while eliminating, for the purpose of clarity, many other elements found in systems and methods of measuring body kinetics for movement disorders and correlating with cognitive and self-assessments. Those of ordinary skill in the art may recognize that other elements and / or steps are desirable and / or required in implementing the present invention. However, because such elements and steps are well known in the art, and because they do not facilitate a better understanding of the present invention, a discussion of such elements andsteps is not provided herein. The disclosure herein is directed to all such variations and modifications to such elements and methods known to those skilled in the art.

[0041] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, exemplary methods and materials are described.

[0042] As used herein, each of the following terms has the meaning associated with it in this section.

[0043] The articles "a" and "an" are used herein to refer to one or to more than one ( / .e., to at least one) of the grammatical object of the article. By way of example, "an element" means one element or more than one element.

[0044] "About" as used herein when referring to a measurable value such as an amount, a temporal duration, and the like, is meant to encompass variations of ±20%, ±10%, ±5%, ±1%, and ±0.1% from the specified value, as such variations are appropriate.

[0045] Ranges: throughout this disclosure, various aspects of the invention can be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Where appropriate, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 2.7, 3, 4, 5, 5.3, and 6. This applies regardless of the breadth of the range.

[0046] Referring now in detail to the drawings, in which like reference numerals indicate like parts or elements throughout the several views, in various embodiments, presented hereinare systems and methods of measuring body kinetics for movement disorders and correlating with cognitive and self-assessments.

[0047] The systems, processes and methods described herein may be utilized for desired practical applications as would be appreciated by those skilled in the art. For example, the systems and methods described herein can be utilized to provide physicians with a holistic "at- home" view of a patient with Parkinson's disease by combining time-sensitive motor assessment, cognitive assessment, and self-assessment, as well as provide suggested medical interventions to improve treatment against the progression of the disease. Furthermore, the systems, processes and methods described herein may be utilized for desired practical applications as would be appreciated by those caring for them. For example, the systems and methods described herein can be utilized to provide caregivers with an easy-to-use tool that helps them record patient symptom information, take assessments, get notified when triggers are detected and monitor medication compliance to improve disease management.

[0048] With reference now to FIG. 1 and FIG. 2, a system 100 for measuring body kinetics for movement disorders is depicted. FIG. 1 depicts the system 100 and FIG. 2 depicts details of sensor units (101, 103) of system 100. The system 100 includes a primary data processing unit (PDPU) 102 including a sensor unit 103 configured to measure body kinetics, and one or more satellite sensor units 101, configured to attached to a body part to measure body kinetics, and communicatively connected to the PDPU 102. In some embodiments, real time kinematics are collected by the satellite sensor units 101 and PDPU sensor unit 103, where real time is defined as less than 500 ms. In some embodiments, body kinetics calculations are performed locally on the PDPU 102 by embedded software (i.e. firmware) to provide for real time analysis, where real time is defined as less than 500 ms.

[0049] In some embodiments, the one or more satellite sensor units 101 comprises at least one of a waist wearable device, a wrist wearable device, and a heel pad device. In some embodiments, the PDPU 102 comprises a wrist wearable device. In some embodiments, the PDPU 102 comprises a waist wearable device. In some embodiments, the PDPU 102 comprises a heel pad device.

[0050] In some embodiments, the sensor unit 103 of the PDPU 102 and the one or more satellite sensor units 101 each comprise a microcontroller 106, a battery 107, a data storage unit 108, a transceiver 113, and an inertial measurement unit (IMU) 109. In some embodiments, the IMU 109 is configured to measure six orthogonal data sets corresponding to body mechanics and movements. In some embodiments, the IMU 109 comprises a gyroscope 110, an accelerometer 111, and can optionally include additional sensors 112 such as a magnetometer and / or other suitable sensors. In some embodiments, the battery 107 comprises a rechargeable battery such as a LiPo cell or other suitable rechargeable cell. In some embodiments, the storage unit 108 comprises RAM, flash RAM, a hard drive, or other suitable storage device or combination thereof. In some embodiments, the microcontroller 106 comprises a real time microcontroller configured to perform real time analysis, real time is defined as less than 500 ms.

[0051] In some embodiments, the PDPU 102 is communicatively connected to an assessment application 105 on a computing system 104, such as the computing system shown in FIG. 6 and described below. In some embodiments, the PDPU 102 and computing system 104 comprise a single device. In some embodiments, the PDPU 102 is wirelessly connected to the computing system 104 via Bluetooth, Bluetooth Low Energy (BLE), Zigbee, Near-Field Communication (NFC), infrared, Wi-Fi, a cellular network connection, or any other suitable wireless connection or combination thereof. In some embodiments, the computing system 104 comprises a desktop computing device, a mobile computing device, a laptop, a tablet, a smartphone, a smart watch, a thin client computing device, a wearable computing device, or any other suitable computing device or combination thereof.

[0052] In some embodiments, the assessment application 105 is configured to perform a cognitive assessment via displaying cognitive assessment questions. The cognitive assessment questions can be based data provided by the system 100 and can further be tailored based on the disorder type. In some embodiments, the assessment application 105 is configured to perform a self-assessment via displaying self-assessment questions.

[0053] In some embodiments, the computing system 104 comprises a processor and a non- transitory computer-readable medium with instructions stored thereon, which when executed by the processor, perform steps comprising a method for correlating body kinetics with cognitive assessments and / or self-assessments for movement disorders, such as method 500 described below and shown in FIG. 5.

[0054] In some embodiments, the one or more satellite sensor units 101 are wirelessly connected to the PDPU 102 via Bluetooth, Bluetooth Low Energy (BLE), Zigbee, Near-Field Communication (NFC), infrared, Wi-Fi, a cellular network connection, or any other suitable wireless connection or combination thereof.

[0055] In some embodiments, the PDPU 102 comprises a processor (such as microcontroller 106) and a non-transitory computer-readable medium (such as data storage unit 108) with instructions stored thereon, which when executed by the processor, perform steps comprising a method for measuring body kinetics for movement disorders, such as method 400 described below and shown in FIG. 4.

[0056] FIGs. 3A-3C show exemplary wearable sensor devices. FIG. 3A shows exemplary waist wearable devices, FIG. 3B shows exemplary heel pads for use in shoes, FIG. 3C shows an exemplary wrist wearable, FIG. 3D shows another embodiment of the exemplary wrist wearable in which the wrist wearable comprises a smart watch or a device of similar form factor, and FIG. 3E shows an exemplary embodiment of the system including a wrist wearable and computing system. In some embodiments the wrist wearable of FIG. 3C or FIG. 3D can be configured as the PDPU 102, but any of the wearable devices of FIGs. 3A-3E can be configured as the PDPU 102. In some embodiments, the wrist wearable further includes a pulse sensor and / or blood oxygenation sensor. In some embodiments, the wrist wearable includes a touchscreen and / or buttons configured as a user interface.

[0057] FIG. 4 is a flow chart depicting an exemplary method 400 for measuring body kinetics for movement disorders. The method 400 starts and Operation 405, where a system for measuring body kinetics for movement disorders, such as system 100 described above, is provided. At operation 410 six orthogonal satellite data sets are collected on the one or moresatellite sensor units 101. The six orthogonal satellite data sets comprise kinematic data with six degrees of freedom. In some embodiments, each satellite sensor 101 collects six orthogonal movement measurements. In some embodiments, the measurements include X, Y and Z axis acceleration, where the axis orientation is arbitrary as long as X, Y and Z are orthogonal, and X, Y and Z rotational acceleration, again where the axis orientation is arbitrary as long as X, Y and Z are orthogonal.

[0058] At Operation 415 the PDPU 102 receives the satellite data sets from the one or more satellite sensor units 101. In some embodiments, the data set receiving is done wirelessly over a protocol such as Bluetooth or other suitable wireless protocols. In some embodiments the data set receiving is done in real time, where real time is defined as less than 500 ms. In some embodiments, the received data sets comprise raw kinematic data.

[0059] At Operation 420 six orthogonal data sets are collected on the sensor unit 103 of the PDPU 102. The six orthogonal data sets comprise kinematic data with six degrees of freedom. In some embodiments, the sensor unit 103 collects six orthogonal movement measurements.In some embodiments, the measurements include X, Y and Z axis acceleration, where the axis orientation is arbitrary as long as X, Y and Z are orthogonal, and X, Y and Z rotational acceleration, again where the axis orientation is arbitrary as long as X, Y and Z are orthogonal.

[0060] At Operation 425 a 3-dimensional linear movement trajectory is calculated based on the orthogonal data sets of the sensor unit 103 of the PDPU 102 and the orthogonal satellite data sets of the one or more satellite sensor units 101. In some embodiments, a three dimensional Euclidian geometry is used to calculate a polar composite linear acceleration vector where the magnitude of that vector is and the direction (trajectory)_1 Y _ 1 y is based on tan (222) on one plane and tan (222) on the other plane. Similar measurements can be made made with the corresponding angular acceleration measurements to construct a composite angular acceleration vector (magnitude and trajectory). In some embodiments, the linear movement trajectory calculation is performed locally on the PDPU 102.

[0061] At Operation 430 a 3-dimensional rotational movement trajectory is calculated based on the orthogonal data sets of the sensor unit 103 of the PDPU 102 and the orthogonal satellite data sets of one or more satellite sensor units 101. In some embodiments, a three dimensional Euclidian geometry is used to calculate a polar composite linear acceleration vector where the magnitude of that vector is Xacc-I- Yacc+ Zaccand the direction (trajectory) —1 Y is based on one plane and tanon the other plane. In someY>accembodiments, the rotational movement trajectory calculation is performed locally on the PDPU 102.

[0062] At Operation 435 the calculated trajectories are combined into a present kinetic state and / or a future kinetic state. In some embodiments, combining of the trajectories is performed locally on the PDPU 102. In some embodiments, the future kinetic state can include fall predictions, FOG episode predictions, and / or any other suitable prediction.

[0063] At Operation 440, the kinetic states are assigned to a corresponding body part. In some embodiments, the assignment is based on sensor type. The assignment can include, for example, a wrist, a foot, a waist, or any other suitable body part. In some embodiments, the assigning is performed locally on the PDPU 102.

[0064] At Operation 445 a correlation of the kinetic states are compared with known movement disorders. In some embodiments, machine learning algorithms are used to determine if the kinetic states correlate to a movement trigger. The correlation is performed between the output of the machine learning algorithms and observationally via patient, caregiver and physician feedback. In some embodiments, the correlation is performed locally on the PDPU 102. In some embodiments, the known movement disorder is associated with Parkinson's disease and comprises freezing of the gait, resting tremor, bradykinesia, dyskinesia, or slowness of movement. In some embodiments, the known movement disorder is associated with Ataxia, Dystonia, Huntington's disease, Parkinson's disease, Tourette syndrome, tremors, or any other movement disorder or combination thereof.

[0065] The method 400 ends at Operation 450, where an event corresponding to a movement disorder is identified when the correlation is above a threshold value. In some embodiments, the identification is performed locally on the PDPU 102.

[0066] FIG. 5 is a flow chart depicting an exemplary method 500 for correlating body kinetics with cognitive and self-assessments for movement disorders. In some embodiments, additional motor assessment tests are also correlated with the body kinetics, cognitive assessment, and / or self-assessment. The method 500 starts at Operation 505, where a movement assessment including a disorder correlation value is provided. In some embodiments, the movement assessment is provided by a system such as system 100 described above. In some embodiments, the movement assessment is the output of a method for measuring body kinetics for movement disorders such as method 400 described above.

[0067] At Operation 510 the disorder correlation value is compared to a threshold value. In some embodiments, machine learning algorithms output an analog score for each movement assessment. In some embodiments, if that score correlates to a greater than 70% confidence level that the disorder is occurring, a trigger is generated.

[0068] At Operation 515, body kinetics data is sent to an assessment application when the disorder correlation value exceeds the threshold value.

[0069] At Operation 520, a cognitive assessment application including cognitive assessment questions based on the disorder type is displayed to a user via a display. In some embodiments the cognitive assessment is displayed on a screen. In some embodiments, the display comprises desktop or mobile devices, laptops, tablets, smartphones, watches, wearable electronics or other wireless digital / cel I ula r phones, televisions, cloud instances, embedded microcontrollers, thin client devices, or any other suitable computing device known in the art. In some embodiments, the cognitive assessment questions are selected from a set of questions based on a trigger or set of triggers comprising the results of the movement assessment, motor assessment, self-assessment, selected answers to current cognitive assessment questions, current dosing details, time since last movement disorder episode, previous dosing recommendation, physician selection, and / or details of previous movement assessments,previous self-assessments, and / or previous cognitive assessments. In some embodiments, example triggers that provoke assessments are freezing of gait, tremor, bradykinesia (slowness of movement) and / or dyskinesia. In some embodiment, these triggers may be generated from the hardware and / or may be invoked by the patient directly. Exemplary cognitive assessment questions include, but are not limited to, simple math questions such as addition, subtraction, multiplication, division, and algebra such as "what is y=2x-4+3x for x=l?", selecting a specific shape from a group of shapes such as, basic memory find it type games where a patient selects hidden objects one at a time revealing the object and then looks for a matching hidden object, completing a maze by tracing a path, trivia questions such as "What is your name?", and "Who is the current president?", or other suitable cognitive assessment questions.

[0070] At Operation 525, a motor assessment application including relevant motor assessments and questions based on the disorder type is displayed to the user via a display. In some embodiments the motor assessment is displayed on a screen. In some embodiments, the display comprises desktop or mobile devices, laptops, tablets, smartphones, watches, wearable electronics or other wireless digital / cel I ula r phones, televisions, cloud instances, embedded microcontrollers, thin client devices, or any other suitable computing device known in the art. In some embodiments, the motor assessment questions are selected from a set of questions based on a trigger or set of triggers comprising the results of the movement assessment, cognitive assessment, self-assessment, selected answers to current motor assessment questions, current dosing details, time since last movement disorder episode, previous dosing recommendation, physician selection, and / or details of previous movement assessments, previous self-assessments, and / or previous cognitive assessments. In some embodiments, example triggers that provoke assessments are freezing of gait, tremor, bradykinesia (slowness of movement) and / or dyskinesia. In some embodiment, these triggers may be generated from the hardware and / or may be invoked by the patient directly. Exemplary motor assessment questions include, but are not limited to, questions relating to reaction time such as "Can you please press the shapes on the screen as quickly as possible when they are highlighted?", questions related to agility such as "Can you please tap your toes on the floor while keeping your heel stationary?", questions related to gait such as "Can you please walk 5 steps forwardwhile keeping your palms facing up?", and questions related to speech such as "Can you please read the following sentence out loud?", or other suitable motor assessment questions.

[0071] At Operation 530, a self-assessment application including self-assessment questions is displayed to the user via a display. In some embodiments the self-assessment is displayed on a screen. In some embodiments, the display comprises desktop or mobile devices, laptops, tablets, smartphones, watches, wearable electronics or other wireless digita l / cel lu la r phones, televisions, cloud instances, embedded microcontrollers, thin client devices, or any other suitable computing device known in the art. In some embodiments, the self-assessment questions are selected from a set of questions based on a trigger or set of triggers comprising the results of the movement assessment, motor assessment, cognitive assessment, selected answers to current self-assessment questions, current dosing details, time since last movement disorder episode, previous dosing recommendation, physician selection, and / or details of previous movement assessments, previous self-assessments, and / or previous cognitive assessments. In some embodiments, example triggers that provoke assessments are freezing of gait, tremor, bradykinesia (slowness of movement) and / or dyskinesia. In some embodiment, these triggers may be generated from the hardware and / or may be invoked by the patient directly. Exemplary self-assessment questions include, but are not limited to, questions pertaining to a patient's diet such as "Have you been eating healthy today?", questions pertaining to a patient's sleep such as "Did you sleep well (8+ hours) last night?", questions pertaining to a patient's stress level such as "How stressed do you feel presently?", or other suitable self-assessment questions.

[0072] In some embodiments, any other suitable additional assessments can also be performed and utilized. One exemplary additional assessment is a caregiver assessment. In some embodiments, when the system 100 detects an event, a caregiver can be notified on a device such as a smart phone running an application that is paired with an application of the patient's personal device. The caregiver application may display questions such as "can you see the patient?", "Is the patient experiencing a tremor event?", "on a scale of 1 to 5 how serious was the tremor event?", or any other suitable caregiver assessment questions based on patient 1disease history, diagnosis, medication dosing, or results of the abovementioned movement, motor, cognitive, and / or self-assessments. A caregiver assessment, in some embodiments, can provide new insights into a patient's disease progression that have not been able to be obtained prior.

[0073] At Operation 535, an event history is constructed combining the cognitive assessment, self-assessment and movement assessment.

[0074] The method 500 ends at Operation 540, where a trend of the cognitive assessment, self-assessment and movement assessment is quantified to determine and predict therapeutic efficiency. The trend can be quantified via any suitable quantification techniques such as linear regression, logistic regression, polynomial regression, stepwise regression, and / or ridge regression.

[0075] In some embodiments, the method 500 further comprises sending a report of the event history and trend to a physician for review. The report can include the results of the movement assessment, cognitive assessment, and / or the self-assessment. With this report a physician can determine a more optimal treatment plan. In some embodiments, the method 500 further comprises calculating a new dosing recommendation and / or physical therapy plan based on the determined and predicted therapeutic efficiency. The new dosing recommendation and / or physical therapy plan can be provided to a physician for review and / or be directly provided to the patient utilizing the system 100. This dosing recommendation can serve to prevent over / under dosing, which gets more difficult as an effective therapy window shrinks over time. In some embodiments, artificial intelligence and / or machine learning are utilized to learn over time and recommend dosing.

[0076] In some embodiments, patient medication history and / or patient activity information are input into the system 100 and utilized to provide a complete causal picture as to what may have triggered movement disorder symptoms and / or events.

[0077] In some aspects of the present invention, software executing the instructions provided herein may be stored on a non-transitory computer-readable medium, wherein thesoftware performs some or all of the steps of the present invention when executed on a processor.

[0078] Aspects of the invention relate to algorithms executed in computer software. Though certain embodiments may be described as written in particular programming languages, or executed on particular operating systems or computing platforms, it is understood that the system and method of the present invention is not limited to any particular computing language, platform, or combination thereof. Software executing the algorithms described herein may be written in any programming language known in the art, compiled or interpreted, including but not limited to C, C++, C#, Objective-C, Java, JavaScript, MATLAB, Python, PHP, Perl, Ruby, or Visual Basic. It is further understood that elements of the present invention may be executed on any acceptable computing platform, including but not limited to a server, a cloud instance, a workstation, a thin client, a mobile device, an embedded microcontroller, a television, or any other suitable computing device known in the art.

[0079] Parts of this invention are described as software running on a computing device. Though software described herein may be disclosed as operating on one particular computing device (e.g. a dedicated server or a workstation), it is understood in the art that software is intrinsically portable and that most software running on a dedicated server may also be run, for the purposes of the present invention, on any of a wide range of devices including desktop or mobile devices, laptops, tablets, smartphones, watches, wearable electronics or other wireless digita l / cel lula r phones, televisions, cloud instances, embedded microcontrollers, thin client devices, or any other suitable computing device known in the art.

[0080] Similarly, parts of this invention are described as communicating over a variety of wireless or wired computer networks. For the purposes of this invention, the words "network", "networked", and "networking" are understood to encompass wired Ethernet, fiber optic connections, wireless connections including any of the various 802.11 standards, cellular WAN infrastructures such as 3G, 4G / LTE, or 5G networks, Bluetooth®, Bluetooth® Low Energy (BLE) or Zigbee® communication links, or any other method by which one electronic device is capableof communicating with another. In some embodiments, elements of the networked portion of the invention may be implemented over a Virtual Private Network (VPN).

[0081] FIG. 6 and the following discussion are intended to provide a brief, general description of a suitable computing environment in which the invention may be implemented. While the invention is described above in the general context of program modules that execute in conjunction with an application program that runs on an operating system on a computer, those skilled in the art will recognize that the invention may also be implemented in combination with other program modules.

[0082] Generally, program modules include routines, programs, components, data structures, and other types of structures that perform particular tasks or implement particular abstract data types. Moreover, those skilled in the art will appreciate that the invention may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[0083] FIG. 6 depicts an illustrative computer architecture for a computer 600 for practicing the various embodiments of the invention. The computer architecture shown in FIG. 6 illustrates a conventional personal computer, including a central processing unit 650 ("CPU"), a system memory 605, including a random-access memory 610 ("RAM") and a read-only memory ("ROM") 615, and a system bus 635 that couples the system memory 605 to the CPU 650. A basic input / output system containing the basic routines that help to transfer information between elements within the computer, such as during startup, is stored in the ROM 615. The computer 600 further includes a storage device 620 for storing an operating system 625, application / program 630, and data.

[0084] The storage device 620 is connected to the CPU 650 through a storage controller (not shown) connected to the bus 635. The storage device 620 and its associated computer-readable media, provide non-volatile storage for the computer 600. Although the description of computer-readable media contained herein refers to a storage device, such as a hard disk or CD-ROM drive, it should be appreciated by those skilled in the art that computer-readable media can be any available media that can be accessed by the computer 600.

[0085] By way of example, and not to be limiting, computer-readable media may comprise computer storage media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROM, DVD, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by the computer.

[0086] According to various embodiments of the invention, the computer 600 may operate in a networked environment using logical connections to remote computers through a network 640, such as TCP / IP network such as the Internet or an intranet. The computer 600 may connect to the network 640 through a network interface unit 645 connected to the bus 635. It should be appreciated that the network interface unit 645 may also be utilized to connect to other types of networks and remote computer systems.

[0087] The computer 600 may also include an input / output controller 655 for receiving and processing input from a number of input / output devices 660, including a keyboard, a mouse, a touchscreen, a camera, a microphone, a controller, a joystick, or other type of input device. Similarly, the input / output controller 655 may provide output to a display screen, a printer, a speaker, or other type of output device. The computer 600 can connect to the input / output device 660 via a wired connection including, but not limited to, fiber optic, ethernet, or copper wire or wireless means including, but not limited to, Bluetooth, Near-Field Communication (NFC), infrared, or other suitable wired or wireless connections.

[0088] As mentioned briefly above, a number of program modules and data files may be stored in the storage device 620 and RAM 610 of the computer 600, including an operating system 625 suitable for controlling the operation of a networked computer. The storage device 620 and RAM 610 may also store one or more applications / programs 630. In particular, the storage device 620 and RAM 610 may store an application / program 630 for providing a variety of functionalities to a user. For instance, the application / program 630 may comprise many types of programs such as a word processing application, a spreadsheet application, a desktop publishing application, a database application, a gaming application, internet browsing application, electronic mail application, messaging application, and the like. According to an embodiment of the present invention, the application / program 630 comprises a multiple functionality software application for providing word processing functionality, slide presentation functionality, spreadsheet functionality, database functionality and the like.

[0089] The computer 600 in some embodiments can include a variety of sensors 665 for monitoring the environment surrounding and the environment internal to the computer 600. These sensors 665 can include a Global Positioning System (GPS) sensor, a photosensitive sensor, a gyroscope, a magnetometer, thermometer, a proximity sensor, an accelerometer, a microphone, biometric sensor, barometer, humidity sensor, radiation sensor, or any other suitable sensor.

[0090] The disclosures of each and every patent, patent application, and publication cited herein are hereby incorporated herein by reference in their entirety. While this invention has been disclosed with reference to specific embodiments, it is apparent that other embodiments and variations of this invention may be devised by others skilled in the art without departing from the true spirit and scope of the invention.

Claims

CLAIMSWhat is claimed is:

1. A system for measuring body kinetics for movement disorders, comprising: a primary data processing unit including a sensor unit, configured to be attached to a first location on a body, further configured to measure body kinetics; and one or more satellite sensor units, configured to be attached to one or more additional locations on a body, further configured to measure body kinetics, and communicatively connected to the primary data processing unit; wherein body kinetics calculations are performed locally on the primary data processing unit.

2. The system of claim 1, wherein the one or more satellite sensor units comprises at least one of a waist wearable device, and a heel pad device, and wherein the primary data processing unit comprises a wrist wearable device.

3. The system of claim 1, wherein the sensor unit of the primary data processing unit and the one or more satellite sensor units each comprise a microcontroller, a battery, a data storage unit, a transceiver, and an inertial measurement unit.

4. The system of claim 3, wherein the inertial measurement unit comprises a gyroscope and an accelerometer.

5. The system of claim 1, wherein the primary data processing unit is communicatively connected to an assessment application on a computing system.

6. The system of claim 5, wherein the primary data processing unit is wirelessly connected to the computing system via a Bluetooth, a Bluetooth Low Energy (BLE), a Zigbee, a Near-Field Communication (NFC), an infrared, a Wi-Fi, or a cellular network connection, and wherein the one or more satellite sensor units are wirelessly connected to the primary data processing unit via a Bluetooth, a Bluetooth Low Energy (BLE), a Zigbee, a Near-Field Communication (NFC), an infrared, a Wi-Fi, or a cellular network connection.

7. The system of claim 5, wherein the computing system comprises a processor and a non- transitory computer-readable medium with instructions stored thereon, which when executed by the processor, perform steps comprising: receiving a movement assessment including a disorder correlation value from the primary data processing unit; comparing the disorder correlation value to a threshold value; sending body kinetics data to an assessment application when the disorder correlation value exceeds the threshold value; displaying a cognitive assessment application including cognitive assessment questions based on the disorder type; displaying a motor assessment application including relevant motor assessments based on the disorder type; displaying a self-assessment application including self-assessment questions; constructing an event history combining the cognitive assessment, self-assessment and movement assessment; and quantifying a trend of the cognitive assessment, self-assessment and movement assessment to determine and predict therapeutic efficiency.

8. The system of claim 5, wherein the computing system comprises a desktop computing device, a mobile computing device, a laptop, a tablet, a smartphone, a smart watch, a thin client computing device, or a wearable computing device.

9. The system of claim 1, wherein the primary data processing unit comprises a processor and a non-transitory computer-readable medium with instructions stored thereon, which when executed by the processor, perform steps comprising: collecting six orthogonal satellite data sets on the one or more satellite sensor units; receiving on the primary data processing unit the satellite data sets from the one or more satellite sensor units; collecting six orthogonal data sets on the sensor unit of the primary data processing unit; calculating a 3-dimensional linear movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units; calculating a 3-dimensional rotational movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units; combining the calculated trajectories into a present kinetic state or a future kinetic state; assigning the kinetic states to a corresponding body part; comparing a correlation of the kinetic states with known movement disorders; and identifying an event corresponding to a movement disorder when the correlation is above a threshold value.

10. A method for measuring body kinetics for movement disorders, comprising: providing the system of claim 1; collecting six orthogonal satellite data sets on the one or more satellite sensor units; receiving on the primary data processing unit the satellite data sets from the one or more satellite sensor units; collecting six orthogonal data sets on the sensor unit of the primary data processing unit;calculating a 3-dimensional linear movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units; calculating a 3-dimensional rotational movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units; combining the calculated trajectories into a present kinetic state or a future kinetic state; assigning the kinetic states to a corresponding body part; comparing a correlation of the kinetic states with known movement disorders; and identifying an event corresponding to a movement disorder when the correlation is above a threshold value.

11. The method of claim 10, wherein the step of receiving on the primary data processing unit the satellite data sets from the one or more satellite sensor units is done in real time.

12. The method of claim 10, wherein the step of receiving on the primary data processing unit the satellite data sets from the one or more satellite sensor units is done wirelessly.

13. The method of claim 10, wherein the steps of calculating a linear movement trajectory, calculating a rotational movement trajectory, combining the trajectories into kinetic states, assigning the kinetic states to a corresponding body part, comparing a correlation, and identifying an event corresponding to a movement disorder are performed locally on the primary data processing unit.

14. The method of claim 10, wherein the corresponding body part comprises a wrist, a waist, or a foot.

15. The method of claim 10, wherein the known movement disorder is associated with Parkinson's disease and comprises freezing of the gait, resting tremor, bradykinesia or slowness of movement, or dyskinesia.

16. A method for correlating body kinetics with cognitive and self-assessments for movement disorders, comprising: providing a movement assessment including a disorder correlation value; comparing the disorder correlation value to a threshold value; sending body kinetics data to an assessment application when the disorder correlation value exceeds the threshold value; displaying a cognitive assessment application including cognitive assessment questions based on the disorder type; displaying a motor assessment application including relevant motor assessments based on the disorder type; displaying a self-assessment application including self-assessment questions; constructing an event history combining the cognitive assessment, self-assessment and movement assessment; and quantifying a trend of the cognitive assessment, self-assessment and movement assessment to determine and predict therapeutic efficiency.

17. The method of claim 16, further comprising sending a report of the event history and trend to a physician for review.

18. The method of claim 16, further comprising calculating a new dosing recommendation or physical therapy plan based on the determined and predicted therapeutic efficiency.

19. The method of claim 16, wherein the step of providing a movement assessment including a disorder correlation value comprises: providing a system for measuring body kinetics for movement disorders comprising:a primary data processing unit including a sensor unit configured to measure body kinetics; and one or more satellite sensor units, configured to attached to a body part to measure body kinetics, and communicatively connected to the primary data processing unit; collecting six orthogonal satellite data sets on the one or more satellite sensor units; receiving on the primary data processing unit the satellite data sets from the one or more satellite sensor units; collecting six orthogonal data sets on the sensor unit of the primary data processing unit; calculating a 3-dimensional linear movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units; calculating a 3-dimensional rotational movement trajectory based on the orthogonal data sets of the sensor unit of the primary data processing unit and the orthogonal satellite data sets of the one or more satellite sensor units; combining the calculated trajectories into a present kinetic state or a future kinetic state; assigning the kinetic states to a corresponding body part; comparing a correlation of the kinetic states with known movement disorders; and identifying an event corresponding to a movement disorder when the correlation is above a threshold value.

20. A method for correlating body kinetics with cognitive, self-assessments, and caregiver assessments for movement disorders; comprising: providing a movement assessment including a disorder correlation value; comparing the disorder correlation value to a threshold value; sending body kinetics data to an assessment application when the disorder correlation value exceeds the threshold value;displaying a cognitive assessment application including cognitive assessment questions based on the disorder type; displaying a motor assessment application including relevant motor assessments based on the disorder type; displaying a self-assessment application including self-assessment questions; displaying a caregiver assessment application including caregiver assessment questions; constructing an event history combining the cognitive assessment, self-assessment, caregiver assessment, and movement assessment; and quantifying a trend of the cognitive assessment, self-assessment, caregiver assessment, and movement assessment to determine and predict therapeutic efficiency.

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