(19) United States
`(12) Patent Application Publication («» Pub. No.: US 2014/0275840 Al
`(43) Pub. Date:
`Sep. 18,2014
`Osorio
`
`US 20140275840A1
`
`(54) PATHOLOGICAL STATE DETECTION USING
`DYNAMICALLY DETERMINED BODY DATA
`VARIABILITY RANGE VALUES
`
`(71) Applicant: Flint Hills Scientific, L.L.C., Lawrence,
`KS (US)
`
`(72)
`
`Inventor: Ivan Osorio, Leawood, KS (US)
`
`(73) Assignee: Flint Hills Scientific, L.L.C., Lawrence,
`KS (US)
`
`(21)
`
`.: 14/208,952
`Appl.No
`
`(22) Filed:
`
`Mar. 13, 2014
`
`Related U.S. Application Data
`(60) Provisional application No. 61/794,540, filed on Mar.
`15, 2013.
`
`100
`
`Publication Classification
`
`(2006.01)
`
`(51) Int.Cl.
`A61B5/00
`(52) U.S. Cl.
`CPC ..................................... A61B 5/4094 (2013.01)
`USPC ............................................................. 600/301
`ABSTRACT
`(57)
`We report a method of detecting a pathological body state of
`a patient, comprising receiving a body signal of the patient;
`determining a BDV from said body signal; determining an
`activity level of said patient; determining a value range for
`said BDV for said patient, based at least in part on said activity
`level; comparing said BDV to said value range; and detecting
`a pathological state when said BDV is outside said value
`range. We also report a medical device system configured to
`implement the method. We also report a non-transitory com­
`puter readable program storage unit encoded with instruc­
`tions that, when executed by a computer, perform the method.
`
`200
`
`COMMUNICATION
`UNIT
`240
`
`KINETIC
`SENSOR(S)
`212
`
`LEAD(S)
`
`211
`
`i™ — — — ”, BODY
`I B0DY | SIGNAL
`■ SIGNAL . LEAD(S)
`j SENSOR(S) j.......y......
`
`I 282 I 281
`I___________ i
`
`["warning"]
`UNIT
`
`291
`
`[”therapy"]
`UNIT
`v
`292
`
`LOGGING
`UNIT
`L""V
`
`__
`SEVERITY
`UNIT
`Lon ocoos oo^ob in« onj
`
`293
`
`294
`
`APPLE 1005
`
`1
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 1 of 12 US 2014/0275840 Al
`
`100
`S
`
`200
`
`KINETIC
`SENSOR(S)
`212
`
`LEAD(S)
`
`211
`
`_____ body
`F BODY | SIGNAL
`I SIGNAL . LEAD(S)
`j SENSOR(S) J-—-y--
`
`282 J 281
`
`WARNING
`UNIT
`
`THERAPY
`UNIT
`
`291
`
`292
`
`LOGGING
`L _UNIL.
`293
`
`SEVERITY
`UNIT
`
`294
`
`FIG. 1
`
`2
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 2 of 12
`
`US 2014/0275840 Al
`
`260
`
`____________________________
`BDV RANGE DETERMINATION MODULE
`
`FIG. 2A
`
`270
`
`FIG. 2B
`
`3
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 3 of 12
`
`US 2014/0275840 Al
`
`265
`
`CURRENT BDV MODULE
`
`1 T q.SAT 1
`RRV ! ! VARIABILITY !
`
`FI
`
` HRV
`
`FIG. 2C
`
`BODY DATA
`VARIABILITY
`(BDV)
`
`FIG. 3
`
`4
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 4 of 12
`
`US 2014/0275840 Al
`
`ACTIVITY
`
`5
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 5 of 12
`
`US 2014/0275840 Al
`
`RESPIRATORY
`RATE
`
`6
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 6 of 12
`
`US 2014/0275840 Al
`
`600
`
`FIG. 6
`
`7
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 7 of 12
`
`US 2014/0275840 Al
`
`700
`
`8
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 8 of 12
`
`US 2014/0275840 Al
`
`riti X
`
`JL. .A. e "kJ*
`
`9
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 9 of 12
`
`US 2014/0275840 Al
`
`900
`
`91CK.
`
`915
`
`BUFFER
`* SIGNAL/FEATURE
`[JN TIME WINDOW J
`
`x Ig EVENT x
`CONFIRMATION
`DESIRED? s
`
`>
`
`[analyze signals"]
`L_ilBUFFER_J
`
`RECEIVE AUTONOMIC,
`METABOLIC, ENDOCRINE,
`NEUROLOGIC, OR TISSUE
`STRESS VARIABILITY DATA
`
`920
`
`CHANGE
`N CURRENT BDV
`VALUE?
`
`NO
`
`YES
`
`930
`
`CHANGE N
`WORKLOAD/K NET C
`ACTIVITY, COGNITIVE
`ACTIVITY, EMOTIONAL
`ACTVTY?
`
`YES
`
`v
`
`CHANGE
`IN BUFFERED
`< SIGNALS OTHER THAN IN
`BDV SIGNAL?
`
`x. YES
`
`NO
`
`NO
`
`ARE
`CHANGES
`COMMENSURATE
`
`960
`
`[cancel WARNING, '
`970 l „ „ USL m _ J
`
`ISSUE EVENT DETECTION,
`WARNING, THERAPY
`DELIVERY AND LOGGING
`(QUANTIFY SEVERITY)
`
`FIG. 9
`
`935
`
`YES
`
`940
`
`V
`
`10
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 10 of 12 US 2014/0275840 Al
`
`1000
`
`1010 X
`
`RECEIVE AUTONOMIC,
`METABOLIC, ENDOCRINE, OR
`TISSUE STRESS VARIABILITY DATA
`
`1020
`
`NO
`
`YES
`
`CHANGE
`N BDV RELAT VETOA
`REFERENCE?
`
`YES
`
`^8-
`
`1030 *
`
`DECREASE?
`
`NO
`
`YES
`
`♦
`
`1040
`
`NCREASE?
`
`YES
`
`YES
`
`COMMENSURATE
`W TH CHANGE N WORK
`LOAD/KNETC
`ACTVTY?
`
`1050
`
`COMMENSURATE
`W TH CHANGE N WORK
`LOAD/KNETC
`ACTVTY?
`
`YES
`
`1060
`
`NO
`
`NO
`
`1070-z
`
`ISSUE EVENT DETECTION,
`WARNING, THERAPY
`DELIVERY, AND LOGGING
`(QUANTIFY SEVERITY)
`
`ISSUE EVENT DETECTION,
`WARNING, THERAPY
`DELIVERY, AND LOGGING 1080
`(QUANTIFY SEVERITY)
`
`FIG. 10
`
`11
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 11 of 12 US 2014/0275840 Al
`
`NON-PATHOLOGSCAL
`
`FIG. 1 1
`
`1200
`
`FIG. 12
`
`12
`
`

`

`Patent Application Publication Sep. 18, 2014 Sheet 12 of 12 US 2014/0275840 Al
`
`1300
`
`FIG. 13
`
`13
`
`

`

`US 2014/0275840 Al
`
`1
`
`Sep. 18,2014
`
`PATHOLOGICAL STATE DETECTION USING
`DYNAMICALLY DETERMINED BODY DATA
`VARIABILITY RANGE VALUES
`
`CROSS-REFERENCE TO RELATED
`APPLICATIONS
`[0001] The present application claims the benefit under 35
`U.S.C. § 119(e) of prior-filed co-pending provisional applica­
`tion No. 61/794,540, filed Mar. 15, 2013; the disclosure of
`which is hereby incorporated by reference.
`
`FIELD OF THE DISCLOSURE
`[0002] This disclosure relates to medical device systems
`and methods capable of detecting a pathological body state of
`a patient, which may include epileptic seizures, and respond­
`ing to the same.
`
`SUMMARY OF THE DISCLOSURE
`[0003] In some embodiments, the present disclosure relates
`to a method of detecting a pathological body state of a patient,
`comprising receiving a body signal of the patient; determin­
`ing a first body data variability (BDV) from said body signal;
`determining an activity level of said patient; determining a
`non-pathological range for said first BDV, based at least in
`part on said activity level; comparing said first BDV to said
`non-pathological range for said first BDV; and detecting a
`pathological body state when said BDV is outside said non-
`pathological range.
`[0004] In some embodiments, the present disclosure relates
`to a method of determining a pathological state in a patient,
`comprising receiving data relating to an activity level of said
`patient; determining an activity level of the patient based on
`said data relating to an activity level; receiving at least one
`body signal of the patient; determining at least a first BDV
`based on said at least one body signal; dynamically determin­
`ing a non-pathological range for said at least a first BDV
`based on said activity level; determining that the patient is in
`one of a non-pathological state and a pathological state,
`wherein said patient is determined to be in a non-pathological
`state if the at least a first BDV is within said non-pathological
`range, and said patient is determined to be in a pathological
`state if the at least a first BDV is outside said non-pathological
`range or is incommensurate for said patient with said activity
`type and level; and taking at least one further action based on
`determining that the patient is in a pathological state, wherein
`said further action is selected from treating said pathological
`state, issuing a warning to the patient or a caregiver regarding
`said pathological state, logging the occurrence of said patho­
`logical state, or logging a severity of said pathological state.
`[0005] In other embodiments, the present disclosure relates
`to a medical device system comprising: at least one activity
`sensor, each said sensor configured to collect at least one
`activity signal from a patient; an activity level module con­
`figured to determine an activity level of said patient, based at
`least in part on said at least one activity signal; at least one
`sensor configured to sense a body signal; a current BDV
`module configured to determine at least a first BDV based on
`said sensed body signal; a BDV range determination module,
`configured to determine a non-pathological BDV range of
`said at least a first BDV, based at least in part on said activity
`type and level; and a state determination module, configured
`to determine that the patient is in one of a non-pathological
`state and a pathological state, wherein said patient is deter­
`
`mined to be in a non-pathological state if the at least a first
`BDV is within said non-pathological BDV range for said at
`least a first BDV, and said patient is determined to be in a
`pathological state if the at least a first BDV is outside said
`non-pathological BDV range for said at least a first BDV.
`[0006] In other embodiments, the present disclosure relates
`to a medical device system, comprising at least one metabolic
`sensor configured to collect at least one metabolic signal or
`respiratory signal relating to an activity level of said patient;
`an activity level module configured to determine an activity
`level of said patient based at least on part on said at least one
`metabolic or respiratory signal; at least one sensor configured
`to sense a body signal; a current BDV module configured to
`determine at least one BDV based on said sensed body signal;
`a BDV range determination module, configured to determine
`a non-pathological BDV range based at least in part on said
`activity level; and a module, configured to determine that the
`patient is in one of a non-pathological state and a pathological
`state, wherein said patient is determined to be in a non-
`pathological state if the first BDV is within said non-patho­
`logical BDV range, and said patient is determined to be in a
`pathological state if the first BDV is outside said non-patho­
`logical BDV range.
`[0007] In some embodiments, the activity refers to physical
`activity (e.g., body movements), while in other embodiments,
`activity refers to cerebral activity (e.g., cognitive, emotional
`or other brain activity).
`[0008] In some embodiments, the present disclosure relates
`to a non-transitory computer readable program storage unit
`encoded with instructions that, when executed by a computer,
`perform a method as described above.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`[0009] The disclosure may be understood by reference to
`the following description taken in conjunction with the
`accompanying drawings, in which like reference numerals
`identify like elements, and in which:
`[0010] FIG. 1 shows a schematic representation of a medi­
`cal device system, according to some embodiments of the
`present disclosure;
`[0011] FIG. 2A shows a schematic representation of a BDV
`range determination module of the medical device system of
`FIG. 1, according to some embodiments of the present dis­
`closure;
`[0012] FIG. 2B shows a schematic representation of an
`additional factor module of the medical device system of FIG.
`1, according to some embodiments of the present disclosure;
`[0013] FIG. 2C shows a schematic representation of a cur­
`rent BDV module of the medical device system of FIG. 1,
`according to some embodiments of the present disclosure;
`[0014] FIG. 3 shows the dynamic nature of an exemplary
`BDV range, according to some embodiments of the present
`disclosure;
`[0015] FIG. 4A shows the dynamic nature of an exemplary
`non-pathological heart rate variability (HRV) range, accord­
`ing to some embodiments of the present disclosure;
`[0016] FIG. 4B shows the dynamic nature of an exemplary
`non-pathological HRV range in more detail, according to
`some embodiments of the present disclosure;
`[0017] FIG. 5 shows the dynamic nature of an exemplary
`non-pathological respiratory rate variability range, according
`to some embodiments of the present disclosure;
`
`14
`
`

`

`US 2014/0275840 Al
`
`2
`
`Sep. 18,2014
`
`[0018] FIG. 6 shows a flowchart representation of a
`method, according to some embodiments of the present dis­
`closure;
`[0019] FIG. 7 shows a flowchart representation of a
`method, according to some embodiments of the present dis­
`closure;
`[0020] FIG. 8 shows a flowchart representation of a
`method, according to some embodiments of the present dis­
`closure;
`[0021] FIG. 9 shows a flowchart representation of a
`method, according to some embodiments of the present dis­
`closure;
`[0022] FIG. 10 shows a flowchart representation of a
`method, according to some embodiments of the present dis­
`closure;
`[0023] FIG. 11 shows a conceptual depiction of pathologi­
`cal and non-pathological BDV (e.g., HRV) ranges, according
`to some embodiments of the present disclosure;
`[0024] FIG. 12 shows a flowchart representation of a
`method, according to some embodiments of the present dis­
`closure; and
`[0025] FIG. 13 shows a flowchart representation of a
`method, according to some embodiments of the present dis­
`closure.
`[0026] While the disclosure is susceptible to various modi­
`fications and alternative forms, specific embodiments thereof
`have been shown by way of example in the drawings and are
`herein described in detail. It should be understood, however,
`that the description herein of specific embodiments is not
`intended to limit the disclosure to the particular forms dis­
`closed, but on the contrary, the intention is to cover all modi­
`fications, equivalents, and alternatives falling within the spirit
`and scope of the disclosure as defined by the appended
`claims.
`
`DETAILED DESCRIPTION OF SPECIFIC
`EMBODIMENTS
`[0027] Illustrative embodiments of the disclosure are
`described herein. For clarity, not all features of an actual
`implementation are described. In the development of any
`actual embodiment, numerous implementation-specific deci­
`sions must be made to achieve design-specific goals, which
`will vary from one implementation to another. Such a devel­
`opment effort, while possibly complex and time-consuming,
`would nevertheless be a routine undertaking for persons of
`ordinary skill in the art having the benefit of this disclosure.
`[0028] Embodiments of the present disclosure provide for a
`medical device capable of monitoring an activity type and/or
`level of a patient and dynamically determining a non-patho-
`logical BDV range based upon an activity type and/or level of
`the patient. The dynamically determined BDV range may be
`used to classify a body system of the patient as being in a
`pathological or non-pathological state. An activity level or
`state (e.g., awake or asleep) of the patient may in some
`embodiments be determined from a kinetic sensor such as an
`accelerometer, while in other embodiments activity level may
`refer to a metabolic activity level as determined from a meta­
`bolic sensor measuring, e.g., glucose consumption, arterial
`and/or venous blood pH or differences thereof, or oxygen
`consumption. Kinetic sensors for use in embodiments herein
`may include any sensor that measures a kinetic activity of the
`patient, including movement, acceleration, velocity, position,
`force, or direction plus duration. The classification of body
`systems of the patient as pathological or non-pathological
`
`may further be based on health status, fitness level and pre­
`vailing environmental conditions (e.g., temperature, altitude,
`humidity, time of day, etc.) or patient characteristics (e.g.,
`age, gender, BMI, fitness level, medications).
`[0029] This disclosure recognizes that to determine (using
`body systems and their features) whether a body system is
`functioning pathologically or non-pathologically with a clini­
`cally worthwhile degree of accuracy and reliability, one must
`take into account the type and/or level of activity being per­
`formed by a subject at the time the pathological/non-patho-
`logical determination is made. For example, if the objective is
`to determine if and when a patient is in a seizure state that
`manifests with increases in heart rate, it is imperative to know
`whether or not a given increase in heart rate is associated with
`a change in activity (e.g., physical or emotional) and if such a
`change in activity is occurring, to determine if the heart rate
`increase is commensurate with said activity type and level.
`This may be accomplished by a dynamical adjustment of
`value ranges of body signal features to avoid false diagnoses.
`[0030] In some embodiments, a non-pathological range for
`a BDV may be dynamically determined (which may include
`an adjustment to a previously determined non-pathological
`BDV range) based on the activity type and/or level of the
`patient. As used herein, the determination or adjustment may
`be considered to be “based on” the activity level so long as the
`determination of the non-pathological range takes into con­
`sideration the activity level, even though other factors (e.g.,
`patient-specific or environmental factors) may also be used to
`determine the non-pathological range. In some embodiments,
`more than one BDV from at least one body signal may be
`determined, and corresponding non-pathological ranges for
`each of the body indices may be determined based on the
`activity type and/or level. Once the non-pathological body
`range is determined, a determination of a pathological or a
`non-pathological state of the patient may be made by com­
`paring the patient’s current BDV to the dynamically deter­
`mined or adjusted non-pathological BDV range. In particular,
`the patient may be determined to be in a non-pathological
`state if the BDV is within the non-pathological BDV range,
`and the patient may be determined to be in a pathological state
`if the first BDV is outside the non-pathological BDV range.
`Where multiple body indices and corresponding non-patho­
`logical body ranges are determined, the determination of a
`pathological or non-pathological state may be based on more
`than one such index and range. When a detection of a patho­
`logical state is made, the medical device may perform a
`responsive action, such as issuing a notice of detection, pro­
`viding a therapy, providing a warning, determining a severity
`of the pathological state, logging the determination of the
`pathological state, logging a time of occurrence of detection,
`logging a response to a therapy, and logging the severity of the
`pathological state.
`[0031] In patients with disorders manifesting with body
`signals whose values are chronically in the pathologic range,
`the aforementioned distinction between pathological and
`non-pathological body signal value ranges no longer applies.
`In this case, variations within the pathologic range, lack of an
`expected variation or a paradoxical “jump” from the patho­
`logical to the non-pathological range value may indicate the
`occurrence of an event.
`[0032] In some embodiments, the present disclosure relates
`to a method of determining a transition to or from a patho­
`logical state in a patient, comprising receiving data related to
`
`15
`
`

`

`US 2014/0275840 Al
`
`3
`
`Sep. 18,2014
`
`oscillations of arterial pressure and smooth muscle sympa­
`thetic nerve activity to determine if the patient is in a patho­
`logical state.
`[0033] FIG. 1 shows a schematic representation of a medi­
`cal device system, according to some embodiments of the
`present disclosure. The medical device system 100 may com­
`prise a medical device 200, activity sensor(s) 212, lead(s) 211
`coupling the activity sensor(s) 212 to the medical device 200,
`body signal sensors 282 and body signal leads 281 coupling
`body signal sensors 282 to medical device 200. The medical
`device system 100 may be fully or partially implanted, or
`alternatively may be fully external. In one embodiment, activ­
`ity sensor(s) 212 may each be configured to collect at least
`one signal from a patient relating to an activity level of the
`patient. In some embodiments, the activity sensor 212 may be
`configured to sense physical, mental, and/or emotional activ­
`ity. For example, each activity sensor 212 may be selected
`from an accelerometer, an inclinometer, a gyroscope, an ergo­
`meter, an electromyography (EMG) sensor, a body tempera­
`ture sensor, an oxygen consumption sensor, a lactic acid
`accumulation sensor, a sweat sensor, a neurogram sensor, a
`force transducer, an ergometer, a responsiveness sensor, or an
`awareness sensor. Brain, metabolic or other sensors may be
`used in some embodiments. For example sensors (electrical,
`thermal, chemical, etc.) may be placed in one more structures
`(e.g., cortex, basal ganglia, cortico-spinal tract, or cerebel­
`lum) involved in motor control to determine the physical
`work performed by a person.
`[0034] Various components of the medical device 200, such
`as controller 210, processor 215, memory 217, power supply
`230, communication unit 240, warning unit 291, therapy unit
`292, and logging unit 293 and severity unit 294 have been
`described in other patent applications assigned to Flint Hills
`Scientific, LLC or Cyberonics, Inc., such as, U.S. application
`Ser. No. 12/770,562, filedApr. 29,2010; U.S. application Ser.
`No. 12/771,727, filedApr. 30,2010; U.S. application Ser. No.
`12/771,783, filedApr. 30, 2010; U.S. application Ser. No.
`12/884,051, filed Sep. 16, 2010; U.S. application Ser. No.
`13/554,367, filed Jul. 20, 2012; U.S. application Ser. No.
`13/554,694, filed Jul. 20, 2012; U.S. application Ser. No.
`13/559,116, filed Jul. 26, 2012; and U.S. application Ser. No.
`13/598,339, filed Aug. 29, 2012; U.S. application Ser. No.
`12/896,525, filed Oct. 1, 2010, now U.S. Pat. No. 8,337,404,
`issued Dec. 25, 2012; U.S. application Ser. No. 13/098,262,
`filedApr. 29, 2011; U.S. application Ser. No. 13/288,886,
`filed Nov. 3,2011; U.S. application Ser. No. 13/554,367, filed
`Jul. 20, 2012; U.S. application Ser. No. 13/554,694, filed Jul.
`20, 2012; U.S. application Ser. No. 13/559,116, filed Jul. 26,
`2012; andU.S. application Ser. No. 13/678,339, filedNov. 15,
`2012. Each of the patent applications identified in this para­
`graph is hereby incorporated herein by reference.
`[0035] The medical device 200 may comprise an activity
`level module 250, configured to determine an activity type
`and/ or level of the patient, based at least in part on body signal
`data collected by activity sensor(s) 212. By “activity level” is
`meant the level of one or more of the patient’s energy con­
`sumption (which may be termed “work level” and may con­
`veniently be measured by proxies such as body movement,
`EMG activity, O2 consumption or heart rate, among others,
`and from which the classical definition of work is not
`excluded), emotional activity (e.g., mild versus intense emo­
`tion), or cognitive activity (e.g., mild versus intense thinking)
`In some embodiments, information relating to work level
`may be collected by an accelerometer, etc., described above.
`
`[0036] The activity level module 250 may determine an
`activity level of the patient at any sampling frequency for
`activity sensors 212. In one embodiment, the activity level
`module 250 is configured to determine the activity level with
`a sampling frequency ranging from about one thousand times
`per second to about once every four hours. The activity level
`module 250 may determine an activity level for at least one
`time window or may determine an instantaneous measure of
`activity. The at least one time window may be on a micro­
`scopic time scale (less than 10 min), a mesoscopic timescale
`(10 min.-24 hr.), or a macroscopic timescale (greater than 24
`hr). Other temporal scales (smaller or larger) than those listed
`above may be applied. The medical device 200 may also
`comprise a BDV range determination module 260, config­
`ured to determine BDV ranges of the patient, based at least in
`part on the activity level determined by the activity level
`module 250. In some embodiments, the BDV range determi­
`nation module 260 may determine a reference value range for
`a certain BDV (e.g., heart rate). In one embodiment, the BDV
`range determination module 260 may determine a non-patho-
`logical range for a particular BDV based on the activity level
`determined by the activity level module 250. By comparing
`an actual BDV (e.g., as determined from a BDV determined
`by a current BDV module 265, based on a body index deter­
`mined by a body index determination module 280) to the
`reference value range (e.g., a non-pathological range), it is
`possible to determine whether the current BDV is in the
`non-pathological range or in a pathological range. Because of
`variations in pathological and non-pathological ranges asso­
`ciated with activity levels, a particular current BDV value
`may indicate that the patient is in a pathological state at one
`activity level but indicate that the patient is in a non-patho­
`logical state at another activity level. Thus, BDV range deter­
`mination module 260 may determine that the same BDV
`value (e.g., the same heart rate) in the same patient is either
`pathological or non-pathological based on the activity level,
`activity type, or other variables (e.g., fitness level). In some
`embodiments, the BDV range determination module 260 may
`determine both a pathological range value and a non-patho­
`logical range value for the one or more body indices. By
`taking into account the effects on body indices of activity
`levels (e.g., mental activity, kinetic activity or metabolic
`activity), non-pathological ranges for particular indices
`derived from monitored body signals may be dynamically
`determined (which includes dynamic adjustment of the indi­
`ces) so that detection of pathological states may be made with
`great accuracy. That is, false negative and false positive detec­
`tions of pathological events may be reduced by dynamically
`determining pathological or non-pathological ranges for par­
`ticular body indices based on activity type and level or other
`variables (e.g., environmental conditions).
`[0037] In some embodiments, ranges determined by the
`BDV range determination module 260 may be based upon
`additional factors beside the activity level of the patient. For
`example, determination of a reference value range (e.g., a
`non-pathological BDV range or a pathological BDV range)
`may, in addition to the activity level of the patient, be based on
`data collected in real-time, and may include patient body data
`and/or environmental conditions that have an influence on the
`non-pathological BDV ranges. These actions may be per­
`formed with or without regard to the patient’s body systems’
`status (normal or abnormal), and adjustments may be made to
`the boundaries of the non-pathological (or pathological)
`range so that a real-time BDV value may, in certain situations
`
`16
`
`

`

`US 2014/0275840 Al
`
`4
`
`Sep. 18,2014
`
`or circumstances, be indicative of a certain pathological state
`(e.g., epileptic seizure) and in others, not be indicative of the
`pathological state. In an adult with a resting heart rate of 110
`bpm (indicative of dysfunction) who also suffers from epi­
`lepsy, seizures may further elevate the heart rate and said
`elevation in the context of no change in activity type or level,
`would be indicative of the occurrence of an epileptic seizure
`in said subject. That is, the collected body data may be a
`priori, normal or abnormal and if abnormal, the occurrence of
`a transient/reversible change in the state of a body system
`may further alter said abnormal activity.
`[0038] In such embodiments, the additional factor(s) may
`be determined by an additional factor module 270 configured
`to determine one or more of a time of day, an environmental
`condition, a patient’s body weight and height, a patient’s
`body mass index, a patient’s gender, a patient’s age, an indi­
`cator of said patient’s overall health, an indicator of said
`patient’s overall fitness, or an indicator of said patient’s level
`of consciousness, and provide an output relating to the addi­
`tional factor determination. The BDV range determination
`module 260 may then be configured to determine a non-
`pathological BDV range based at least in part on the output of
`the additional factor module 270.
`[0039] The BDV range determination module 260 may be
`configured to determine said reference value range (e.g., non-
`pathological or pathological BDV range) based at least in part
`on a kinetic signal collected from a time window ending at the
`current time. In some embodiments, the BDV range determi­
`nation module 260 may perform calculations based upon a
`moving time window used to collect body signals.
`[0040] In one embodiment, the BDV range determination
`module 260 may be configured to determine a non-pathologi-
`cal range for a first time based on the patient’s activity in a first
`time window prior to said first time. The first time window
`may comprise a time interval ranging from 1 second to two
`hours. In one embodiment, the first time window may com­
`prise one of: said first time and the preceding 1 second; said
`first time and the preceding 10 seconds; said first time and the
`preceding 30 second; said first time and the preceding 1
`minute; said first time and the preceding 2 minutes; said first
`time and the preceding 3 minutes; said first time and the
`preceding 5 minutes; said first time and the preceding 10
`minutes; said first time and the preceding 30 minutes; said
`first time and the preceding 1 hour; said first time and the
`preceding 2 hours. In some embodiments, the BDV range
`determination module 260 may also use the patient’s histori­
`cal health information to generate a non-pathological range
`for one or more body indices. Historical data of the patient
`may allow determination of changes in non-pathological
`ranges of the BDV during certain time periods.
`[0041] The BDV range determination module 260 may
`make its determination at any sampling frequency or sam­
`pling rate. In one embodiment, the BDV range determination
`module 260 is configured to determine a non-pathological
`BDV range for a BDV (e.g., an instantaneous or average heart
`rate) at an update frequency ranging from about one thousand
`times per second to about once every four hours.
`[0042] The medical device 200 may further comprise a
`body index determination module 280, configured to deter­
`mine one or more body indices of the patient. The body index
`may be heart rate (instantaneous or in a short-term or long­
`term time window), heart rate rhythm, heart rate variability,
`blood pressure, blood pressure variability, respiratory rate,
`respiratory rhythm, respiratory rate variability, end tidal CO2,
`
`kinetic activity, cognitive activity, dermal (including electro-
`dermal) activity, chemical (including electro-chemical) activ­
`ity, arterial pH, venous pH, arterial-venous pH difference,
`cortisol level, catecholamine level, or blood oxygen satura­
`tion, among others. The body index may be determined based
`on a signal collected from one or more body signal sensor(s)
`282, which may be coupled to the medical device 200 by body
`signal lead(s) 281.
`[0043] The medical device 200 may comprise a current
`BDV module 265 configured to determine at least one BDV.
`The current BDV module 265 may be configured to deter­
`mine at least one body data variability selected from a heart
`rhythm variability, a heart rate variability (HRV), a respira­
`tory rate variability (RRV), a blood pressure variability
`(BPV), a respiratory rhythm variability, respiratory sinus
`arrhythmia, end tidal CO2 concentration variability, power
`variability at a certain neurological index frequency band
`(e.g., beta), an EKG morphology variability, a heart rate pat­
`tern variability, an electrodermal variability (e.g., a skin resis­
`tivity variability or a skin conductivity variability), a pupil­
`lary diameter variability, a blood oxygen saturation
`variability, a kinetic activity variability, a cognitive activity
`variability, arterial pH variability, venous pH variability, arte­
`rial-venous pH difference variability, a lactic acid concentra­
`tion variability, a cortisol level variability, or a catecholamine
`level variability. The current BDV module 265 may be con­
`figured to determine the BDV from a body index determined
`by body index determination module 280. BDV may be
`expressed as a range of values [min-max], their variance or
`their standard deviation.
`[0044] The medical device 200 may further comprise a
`pathological state determination module 290, configured to
`determine an occurrence of a pathological state of the patient,
`in response to the BDV being outside of a non-pathological
`range for the BDV for the prevailing activity type, level and
`other conditions. An occurrence of any pathological state that
`may be associated with a body signal outside a non-patho­
`logical BDV range provided by analysis of the patient’s activ­
`ity level may be determined by the pathological state occur­
`rence module 290.
`[0045] In patients whose baseline BDV range is abnormal,
`the occurrence of a seizure may manifest by an increase in
`BDV (i.e., the BDV value becomes even more abnormal), or
`in other cases, by the BDV decreasing into what generally
`among the patient population is the normal or non-pathologi­
`cal range. This latter concept may be referred to as “paradoxi­
`cal normalization” For example, in an epilepsy patie