This invention generally relates to Transcutaneous Electrical Nerve Stimulation (TENS) devices that deliver electrical currents across the intact skin of a user in order to provide symptomatic relief of chronic pain, and more particularly to TENS devices configured for automated compensation for circadian rhythms and other temporal variations in the user's physiology.
Transcutaneous electrical nerve stimulation (TENS) is the delivery of electricity (i.e., electrical stimulation) across the intact surface of a user's skin in order to activate sensory nerve fibers. The most common application of TENS therapy is to provide analgesia, such as for chronic pain. Other applications of TENS therapy include, but are not limited to, reducing the symptoms of restless leg syndrome, decreasing nocturnal muscle cramps, and providing relief from generalized pruritis. A conceptual model for how sensory nerve stimulation leads to pain relief was proposed by Melzack and Wall in 1965. Their theory stipulates that activation of sensory nerves (Aβ fibers) closes a “pain gate” in the spinal cord that inhibits the transmission of pain signals carried by nociceptive afferents (C and Aδ fibers) to the brain. In the past 20 years, anatomic pathways and molecular mechanisms that may underlie the pain gate have been identified. Sensory nerve stimulation (e.g., via TENS) activates the descending pain inhibition system, primarily the periaqueductal gray (PAG) and rostroventral medial medulla (RVM) located in the midbrain and medulla sections of the brainstem, respectively. The PAG has neural projections to the RVM, which in turn has diffuse bilateral projections into the spinal cord dorsal horn that inhibit ascending pain signal transmission.
TENS is typically delivered in short discrete pulses (with each pulse typically being several hundred microseconds in duration) at frequencies between about 10 and 150 Hz, through hydrogel electrodes placed on the user's body. TENS is characterized by a number of electrical parameters including the amplitude and shape of the stimulation pulse (which combine to establish the pulse charge), the frequency and pattern of the pulses, the duration of a therapy session and the interval between therapy sessions. All of these parameters are correlated to the therapeutic dose. For example, higher amplitude and longer pulses (i.e., larger pulse charge) increase the dose, whereas shorter therapy sessions decrease the dose. Clinical studies suggest that pulse charge and therapy session duration have the greatest impact on therapeutic dose.
To achieve maximum pain relief (i.e., hypoalgesia), TENS needs to be delivered at an adequate stimulation intensity. Intensities below the threshold of sensation are not clinically effective. The optimal therapeutic intensity is often described as one that is “strong yet comfortable”. Most TENS devices rely on the user to set the stimulation intensity, usually through a manual intensity control comprising an analog intensity knob or digital intensity control push-buttons. In either case (i.e., analog control or digital control), the user must manually increase the intensity of the stimulation to what the user believes to be a therapeutic level. Therefore, a major limitation of current TENS devices is that it may be difficult for many users to determine an appropriate therapeutic stimulation intensity. As a result, the user will either require substantial support from medical staff or they may fail to get pain relief due to an inadequate stimulation level.
A newly-developed wearable TENS device (Quell®, Neurometrix, Inc., Waltham, Mass., USA) uses a novel method for calibrating the stimulation intensity in order to maximize the probability that the TENS stimulation intensity will fall within the therapeutic range. With the Quell® device, the user identifies their electrotactile sensation threshold and then the therapeutic intensity is automatically estimated by the TENS device based on the identified electrotactile sensation threshold.
Pain relief from TENS stimulation usually begins within 15 minutes of the stimulation onset and may last up to an hour following the completion of the stimulation period (also known as a “therapy session”). Each therapy session typically runs for 30-60 minutes. To maintain pain relief (i.e., hypoalgesia), TENS therapy sessions typically need to be initiated at regular intervals. Newly-developed wearable TENS devices, such as the aforementioned Quell® device, provide the user with an option to automatically restart therapy sessions at pre-determined time intervals.
The persistent nature of chronic pain and the convenience of “wear-and-forget” TENS technology may lead some users to wear the TENS device daily for an extended period of time. To achieve maximum pain relief, TENS needs to be delivered at an adequate stimulation intensity level throughout the day and also at night (i.e., when the user is asleep). The optimal therapeutic stimulation intensity level varies from person to person, and depends upon the electrotactile threshold of each individual user. Once the optimal setting for the therapeutic stimulation intensity level is determined for a particular user, it remains fixed for that user for all subsequent TENS therapeutic sessions throughout the day.
However, all organisms have internal “clocks” that regulate normal biological processes and normal physiological function. The most important and well understood internal “clock” is the circadian rhythm. In the absence of external entrainment cues, the human circadian rhythm has a 20 to 28 hour cycle. The circadian oscillator is synchronized to the physical 24-hour day-night cycle by environmental signals such as light. Therefore, a single time-invariant TENS dose may not provide consistent pain relief throughout the day for a TENS user.
A growing recognition of the importance of the circadian rhythm, and other temporal fluctuations, in various diseases and the efficacy of their treatments has led to the concept of “chronotherapy,” which is an attempt to design therapeutic approaches that account for the temporal properties of human physiological function. By way of example but not limitation, circadian rhythms influence chronic pain and may impact the treatment of pain using TENS therapy. Variations in pain intensity over the course of the day are common. Some pain conditions, such as painful diabetic neuropathy, exhibit peak intensity (i.e., the greatest level of pain) in the evening, while other pain conditions, such as fibromyalgia, exhibit peak intensity (i.e., the greatest level of pain) in the morning. One significant implication of these fluctuations in the degree of pain experienced by the user over the course of the day is that a user may require a higher therapeutic dose (i.e., a higher level of TENS stimulation) at certain times of the day in order to achieve optimal and stable pain control.
A user's sensory threshold may vary over the course of the day, which may also impact the efficacy of TENS therapy at a given stimulation intensity level. In other words, the threshold at which a sensory stimulus (e.g., electrical stimulation, light, heat, etc.) is detected by the user is not constant, but varies over the course of the 24-hour cycle. Although, circadian variation in the perception threshold to electrical stimulation, commonly referred to as the “electrotactile threshold”, has not been studied extensively, several published studies suggest that humans experience time-varying perception thresholds to electrical stimulation (e.g., TENS therapy). Most users experience their lowest perception threshold (i.e., greatest sensitivity) to electrical stimulation (e.g., TENS therapy) in the late afternoon and early evening (see, for example, Sheriden et al., “Some Factors Influencing the Threshold of the Electrocutaneous Stimulus”. Percept. Mot. Skills, 1966). However, there is substantial inter-individual variation and some users experience a minimum perception threshold at other times of the day. The implication of a varying electrotactile perception threshold is that the therapeutic effect of TENS stimulation therapy may vary in a circadian fashion if the stimulation intensity is held constant throughout the day. More particularly, if the user's electrotactile perception threshold is low, then more sensory nerves will be stimulated as compared to when the user's electrotactile perception threshold is high.
The anatomical location where circadian modulation occurs may be in the periphery of the user's body, in the user's central nervous system (CNS), or both. In the periphery of the user's body, modulation of nerve stimulation may be due to changes in body surface temperature, biophysical changes in peripheral nerve membranes, and other effects. Circadian rhythms may also modulate sensory perception in the CNS where the integration of peripheral sensory signals may be amplified or attenuated in a time-varying fashion. Regardless of the site(s) of circadian control/modulation of the electrotactile perception threshold, the net effect is that the sensory input that triggers the descending pain inhibition system fluctuates in a rhythmic fashion, leading to an oscillation in the effective stimulation intensity. To maintain stable and uniform therapeutic effectiveness of TENS therapy for a particular user, the circadian rhythms of that particular user can be exploited in order to optimally regulate TENS stimulation parameters, with the goal of enhancing TENS therapeutic effectiveness by counteracting the time-dependent nature of the sensory perception threshold and pain level.
The present invention comprises the provision and use of a novel TENS device which comprises a stimulator designed to be placed on a user's upper calf (or other anatomical location) and a pre-configured electrode array designed to provide electrical stimulation to at least one nerve disposed in the user's upper calf (or other anatomical location). A key feature of the present invention is that the novel TENS device automatically adjusts stimulation parameters according to the time of day in order to compensate for circadian rhythms and other temporal variations in the user's physiology.
In one preferred form of the present invention, there is provided apparatus for transcutaneous electrical nerve stimulation in a user, the apparatus comprising:
stimulation means for electrically stimulating at least one nerve with at least one stimulation pulse;
control means connected to said stimulation means for controlling at least one characteristic of said at least one stimulation pulse; and
modulating means connected to the control means for modulating said at least one characteristic of said at least one stimulation pulse according to the time of day.
In another preferred form of the present invention, there is provided a method for controlling transcutaneous electrical nerve stimulation based on the time of day, the method comprising the steps of:
providing apparatus for transcutaneous electrical nerve stimulation in a user, the apparatus comprising:
determining a time-varying function within a 24-hour period;
using said stimulation means to electrically stimulate at least one nerve; and
modulating at least one characteristic of said electrical stimulation according to the time of day and said time-varying function.
These and other objects and features of the present invention will be more fully disclosed or rendered obvious by the following detailed description of the preferred embodiments of the invention, which is to be considered together with the accompanying drawings wherein like numbers refer to like parts, and further wherein:
The present invention comprises the provision and use of a novel TENS device which comprises a stimulator designed to be placed on a user's upper calf (or other anatomical location) and a pre-configured electrode array designed to provide electrical stimulation to at least one nerve disposed in the user's upper calf (or other anatomical location). A key feature of the present invention is that the novel TENS device automatically adjusts stimulation parameters according to the time of day.
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As discussed above, temperature sensor 107 is preferably disposed within compartment 102 of stimulator 105. However, it should be appreciated that, if desired, temperature sensor 107 may be embedded in the strap 110 (e.g., in the manner shown in
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In one preferred form of the invention, TENS device 100 is configured to be worn on the user's upper calf 140 as shown in
Electrical current (i.e., for therapeutic electrical stimulation to the tissue) is provided to the electrode pairs 154, 156 and 152, 158 by connectors 160, 162 which mate with complementary connectors 210, 212, respectively, on stimulator 105 (see
In one preferred embodiment of the present invention, the skin-contacting conductive material of electrodes 152, 154, 156, 158 is a hydrogel material which is “built into” electrodes 152, 154, 156, 158. The function of the hydrogel material on the electrodes is to serve as an interface between the electrodes 152, 154, 156, 158 and the skin of the user (i.e., within, or adjacent to, or proximal to, the portion of the user's body in which the sensory nerves which are to be stimulated reside). Other types of electrodes such as dry electrodes and non-contact stimulation electrodes have also been contemplated.
In prior U.S. patent application Ser. No. 13/678,221, filed Nov. 15, 2012 by Neurometrix, Inc. and Shai N. Gozani et al. for APPARATUS AND METHOD FOR RELIEVING PAIN USING TRANSCUTANEOUS ELECTRICAL NERVE STIMULATION, issued as U.S. Pat. No. 8,948,876 on Feb. 3, 2015, which patent is hereby incorporated herein by reference, apparatus and methods are disclosed for allowing a user to personalize TENS therapy stimulation intensity according to the electrotactile perception threshold of the user at the time of the setup of the TENS device. U.S. Pat. No. 8,948,876 also discloses apparatus and methods to automatically restart additional therapy sessions after an initial manual start by the user. In prior U.S. patent application Ser. No. 14/230,648, filed Mar. 31, 2014 by NeuroMetrix, Inc. and Shai Gozani et al. for DETECTING CUTANEOUS ELECTRODE PEELING USING ELECTRODE-SKIN IMPEDANCE, issued as U.S. Pat. No. 9,474,898 on Oct. 25, 2016, which patent is hereby incorporated herein by reference, apparatus and methods are disclosed which allow safe delivery of TENS therapies at night when the user is asleep. These methods and apparatus allow the TENS device to be worn by a user for an extended period of time, including 24 hours a day.
A fixed TENS stimulation level may not be appropriate to deliver consistently comfortable and effective pain relief to a user throughout both the day and the night, since the impact of circadian or other time-varying rhythms mitigates the effectiveness of TENS stimulation. Parameters impacting TENS stimulation effectiveness include, but are not limited to, stimulation pulse amplitude 493 and pulse width 494, pulse frequency 495, and therapy session duration 482. By way of example but not limitation, higher amplitude and longer pulses (i.e., larger pulse charge) increase the stimulation delivered to the user (i.e., the stimulation “dose”), whereas shorter therapy sessions decrease stimulation delivered to the user (i.e., the stimulation “dose”). Clinical studies suggest that pulse charge (i.e., pulse amplitude and pulse width) and therapy session duration have the greatest impact on the therapeutic stimulation delivered to the user (i.e., the therapeutic stimulation “dose”).
One object of the present invention is to permit TENS device 100 to automatically offset the impact of circadian or other time-varying rhythms on the comfort and efficacy of TENS stimulation therapy, where efficacy is usually considered to be analgesia (i.e., the alleviation of pain) but may also be viewed more broadly in terms of other clinical effects of TENS such as, but not limited to, therapy for sleep disorders, therapy for muscle cramps, and therapy for treating pruritis. More particularly, the present invention automatically modulates at least one TENS stimulation parameter in order to compensate for the effect of at least one circadian rhythm. By way of example but not limitation, as previously discussed, it is known that an individual's electrotactile perception threshold varies over the course of a day in a circadian fashion.
In one preferred form of the present invention, the modulated stimulation parameters are pulse amplitude 493 and pulse width 494, or a combination of pulse amplitude 493 and pulse width 494 (pulse charge), since these stimulation parameters are known to have a direct impact on both comfort and analgesic efficacy. In another form of the invention, the modulated stimulation parameter is the pulse frequency 495. In yet another form of the invention, the modulated stimulation parameter is the duration of the therapy session 482. In another form of the invention, the modulated stimulation parameter is the elapsed time between consecutive therapy sessions. Modulation of other stimulation parameters, or combinations of stimulation parameters, falls within the scope of the present invention. By way of example but not limitation, in one form of the invention, the pulse charge and the pulse frequency are concurrently regulated in order to compensate for one or more circadian rhythms.
In one preferred form of the invention, the automatic compensation for temporal fluctuations (i.e., the automatic modulation of one or more stimulation parameters) is accomplished through a time-dependent function that offsets the actual stimulation intensity delivered to the user by TENS device 100. In the case of a circadian rhythm, this compensation is sometimes hereinafter called a circadian compensation function (CCF). The CCF modulates an electrical stimulation parameter during TENS therapy so as to offset the effect of a circadian rhythm on TENS therapy. In a preferred form of the invention, the stimulation parameter p(t) is modulated by a time-varying factor Δ(t),as described by Equation 1,
Δ(t)=A sin(ωt−δ) Eq. 1
where ω is the angular frequency of the circadian rhythm. In the preferred embodiment, we assume that the user has a normal circadian rhythm that is entrained to the day night 24-hour cycle (86,400 seconds). Therefore, the angular frequency is 2π/86400 or 72.7×10−6 radians (i.e., sec−1). t is the time of day measured in seconds. δ is the phase delay in radians. A is the magnitude of the circadian compensation factor, usually represented in decibels. In a preferred form of the invention, the circadian compensation factor has a value of 0.5 dB, although values from 0.5 to 2 dB are common. If both p(t) and Δ(t) are expressed in decibels, then the modified time-varying electrical parameter pm(t) is given by Equation 2,
pm(t)=p(t)+Δ(t) Eq. 2
With A=0.5 dB, the CCF modulates the stimulation intensity by a multiplicative factor ranging from 0.94 to 1.06 (i.e., approximately ±6%). For example, if the purpose of the CCF is to regulate pulse charge with a baseline value of 10 μC, then the CCF will modulate the pulse charge from 9.4 μC to 10.6 μC depending on the time of day. δ is the phase delay of the circadian rhythm, measured in radians.
An important assumption implicit in the CCF of Equation 1 is that the circadian rhythm follows a sinusoidal pattern. Circadian rhythms typically exhibit features of sinusoidal rhythms, repeatedly ascending to a maximum value, steadily decreasing to a minimum value and then increasing again. Therefore, mathematical models of circadian rhythms often utilize sine and cosine functions. This approach appears to provide a good fit to many types of circadian data such as core body temperature. In some instances, non-sinusoidal shapes such as square wave or triangle wave approximations better match the data. Although the preferred embodiment utilizes a sinusoidal function, alternative circadian rhythm models may be used and fall within the scope of the invention.
The CCF must be customized for each user. The most straightforward approach for customizing the CCF for each user is to ask the user what time of the day the uncompensated TENS stimulation feels strongest in the case of constructing a circadian rhythm of the electrotactial perception threshold. Similarly, a circadian rhythm for the pain intensity is constructed by identifying the time when is the pain level is the greatest. In one preferred embodiment, the CCF is then “shifted” in time to match the specified timing information provided by the user. Another approach to customize the CCF for individuals is to measure relevant physiological parameters such as skin temperature, skin impedance, and Galvanic skin response over the course of a day. Measurements from several days can also be used to calculate an average CCF (i.e., by using a processor included in TENS device 100 for creating a circadian compensation profile and determining compensation values, as will hereinafter be discussed in further detail). In another form of the invention, measured physiological values as a function of measurement time are used by the processor 515 to calculate the CCF. In yet another form of the invention, a suitable function with parametric model parameters is fitted to the measured values to calculate the CCF. And in another form of the invention, an initial CCF profile can be created based on demographic and physiological characteristics of the user, which may be used to calculate the CCF for a particular user. Subsequently manual adjustments of TENS stimulation parameters by the user can be used to refine the initial (i.e., calculated) CCF.
The circadian compensation function (CCF) represented in Equation 1 can be expanded to account for more than one simultaneous sinusoidal circadian rhythm, with each of the multiple simultaneous sinusoidal circadian rhythms being approximated by a sinusoid as represented in Equation 3,
Δ(t)=Σi=1NAi sin(ωt+δi) Eq. 3
Where Ai is the amplitude and δi is the phase of the ith circadian rhythm. This generalized model makes a number of assumptions. Most notably, this generalized model assumes that the impact of multiple circadian rhythms on TENS are independent. As a result, the individual circadian compensation functions can be summed to create a composite circadian compensation function that will compensate for the integrated effect of the individual circadian rhythms. This is a reasonable first order approximation. The more generalized model can be written as shown in Equation 4,
Δ(t)=A sin(ωt+ϕ) Eq. 4
where A and ϕ are functions of both {A1 . . . AN} and {δ1 . . . δN}. In one form of the invention, the individual circadian rhythms may not have an independent effect on TENS. In other words, there may be cross-interactions between the individual circadian rhythms.
In one preferred form of the invention, circadian compensation of multiple circadian rhythms is accomplished through modulation of one stimulation parameter, such as stimulation pulse intensity. In another preferred form of the invention, circadian compensation is achieved through modulation of multiple stimulation parameters (e.g., stimulation pulse intensity and time delay between stimulation sessions). An example is illustrated via
In one preferred form of the invention, TENS device 100 comprises a circadian rhythm processor 515 and a controller 520. TENS device 100 is configured/programmed to operate in the manner shown in
More particularly, when TENS device 100 is secured to the upper calf 140 of the user and turned on, processor 515 collects data from accelerometer 172, real-time clock 505, temperature sensor 107, ambient light detector 510, and skin impedance and Galvanic response detector 109. Time from real-time clock 505 is used to determine the compensation values. User state (e.g., active, asleep, rest) based on accelerometer 172 and/or other sensors (e.g., light detector 510, temperature sensor 107, etc.) can also be used to determine the compensation values at a given time.
A compensation profile is created by processor 515 using a pre-loaded compensation profile which is universal to all TENS users (i.e., a pre-loaded compensation profile which is already stored in TENS device 100, i.e., in appropriate hardware and software of the sort well known in the art). The pre-loaded compensation profile can also be based on disease state transmitted from a user input module 512 or pain intensity profile transmitted from user input module 512. It should be appreciated that user input module 512 may comprise a data connection (e.g., a USB cable) tethered to an external computer, a wireless connection to a smartphone 860 configured with appropriate software for permitting user input and wirelessly communicating with TENS device 100, etc.). The compensation profile can be based on (or updated in response to) physiological measurements from skin temperature sensor 107, or the skin impedance and a Galvanic response detector 109 (
The compensation value calculated by the processor 515 is transmitted to the controller 520. The controller 520 in turn modifies one or more stimulation parameters such as stimulation pulse intensity, pulse width, pulse frequency, therapy session duration, or the time delay between sessions in order to deliver the optimal and stable pain control.
Data from skin impedance and Galvanic response detector 109, temperature sensor 107, or accelerometer 172 can be used to determine the pain-relieving effect of the TENS stimulation. By way of example but not limitation, more restful sleep at night can be quantified by the accelerometer data (i.e., since more restful sleep results in less movement of the user's body). If sleep measurements improve with the introduction of a modification to the circadian compensation profile, then the processor 515 can incorporate that information to strengthen the modification. If the sleep quality degenerates with a change to the compensation profile, processor 515 may discount the change to the compensation profile.
It should be understood that many additional changes in the details, materials, steps and arrangements of parts, which have been herein described and illustrated in order to explain the nature of the present invention, may be made by those skilled in the art while still remaining within the principles and scope of the invention.
This patent application: (i) is a continuation-in-part of pending prior U.S. patent application Ser. No. 14/253,628, filed Apr. 15, 2014 by Neurometrix, Inc. and Shai Gozani et al. for TRANSCUTANEOUS ELECTRICAL NERVE STIMULATOR WITH AUTOMATIC DETECTION OF USER SLEEP-WAKE STATE; and (ii) claims benefit of prior U.S. Provisional Patent Application Ser. No. 62/361,698, filed Jul. 13, 2016 by NeuroMetrix, Inc. and Shai N. Gozani for APPARATUS AND METHOD FOR AUTOMATED COMPENSATION OF TRANSCUTANEOUS ELECTRICAL NERVE STIMULATION FOR CIRCADIAN RHYTHMS, which patent application is hereby incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
1741962 | Theodoropulos | Dec 1929 | A |
D263869 | Sumiyasu | Apr 1982 | S |
4503863 | Katims | Mar 1985 | A |
4605010 | McEwen | Aug 1986 | A |
4738250 | Fulkerson et al. | Apr 1988 | A |
4989605 | Rossen | Feb 1991 | A |
5048523 | Yamasawa et al. | Sep 1991 | A |
5063929 | Bartelt et al. | Nov 1991 | A |
5121747 | Andrews | Jun 1992 | A |
5169384 | Bosniak et al. | Dec 1992 | A |
D342571 | Givens, Sr. | Dec 1993 | S |
D346029 | Shalvi | Apr 1994 | S |
5350414 | Kolen | Sep 1994 | A |
5429589 | Cartmell et al. | Jul 1995 | A |
5479939 | Ogino | Jan 1996 | A |
5487759 | Bastyr et al. | Jan 1996 | A |
5562718 | Palermo | Oct 1996 | A |
5806522 | Katims | Sep 1998 | A |
D411887 | Agarwala | Jul 1999 | S |
5948000 | Larsen et al. | Sep 1999 | A |
6099488 | Hung | Aug 2000 | A |
6161044 | Silverstone | Dec 2000 | A |
6266558 | Gozani et al. | Jul 2001 | B1 |
D450313 | Koinuma | Nov 2001 | S |
6430450 | Bach-y-Rita et al. | Aug 2002 | B1 |
D462772 | Lamping et al. | Sep 2002 | S |
6456884 | Kenney | Sep 2002 | B1 |
6662051 | Eraker et al. | Dec 2003 | B1 |
D541042 | Andre et al. | Apr 2007 | S |
D566383 | Harris et al. | Apr 2008 | S |
D592200 | Liu | May 2009 | S |
D598556 | Chen | Aug 2009 | S |
D600352 | Cryan | Sep 2009 | S |
D607198 | Andre et al. | Jan 2010 | S |
D609353 | Cryan | Feb 2010 | S |
7668598 | Herregraven et al. | Feb 2010 | B2 |
D611611 | Sachi et al. | Mar 2010 | S |
D615526 | Andre et al. | May 2010 | S |
7720548 | King | May 2010 | B2 |
7725193 | Chu | May 2010 | B1 |
7787946 | Stahmann et al. | Aug 2010 | B2 |
D625829 | Arbesman et al. | Oct 2010 | S |
D629115 | Robertson | Dec 2010 | S |
D636881 | Clemens et al. | Apr 2011 | S |
D637988 | Jinkinson | May 2011 | S |
8108049 | King | Jan 2012 | B2 |
8121702 | King | Feb 2012 | B2 |
8131374 | Moore et al. | Mar 2012 | B2 |
D658302 | Nixon | Apr 2012 | S |
D680735 | Itabashi et al. | Apr 2013 | S |
8421642 | McIntosh et al. | Apr 2013 | B1 |
D688707 | Vincent et al. | Aug 2013 | S |
D705428 | Cheney et al. | May 2014 | S |
D712045 | Thornton | Aug 2014 | S |
8825175 | King | Sep 2014 | B2 |
8862238 | Rahimi et al. | Oct 2014 | B2 |
D716963 | Yosef et al. | Nov 2014 | S |
8948876 | Gozani | Feb 2015 | B2 |
D732682 | Porat | Jun 2015 | S |
9168375 | Rahimi et al. | Oct 2015 | B2 |
D744661 | Rizzi | Dec 2015 | S |
D750263 | Shigeno et al. | Feb 2016 | S |
D750798 | Yosef et al. | Mar 2016 | S |
D754355 | Ganapathy et al. | Apr 2016 | S |
D754973 | Danze et al. | May 2016 | S |
D757292 | Chen | May 2016 | S |
D758605 | Chen | Jun 2016 | S |
D758606 | Chen | Jun 2016 | S |
D759262 | Chen | Jun 2016 | S |
D759263 | Chen | Jun 2016 | S |
D759958 | Requa | Jun 2016 | S |
D762628 | Yoon et al. | Aug 2016 | S |
D762872 | Chen | Aug 2016 | S |
D767775 | Gilmer et al. | Sep 2016 | S |
9452287 | Rosenbluth | Sep 2016 | B2 |
9474898 | Gozani et al. | Oct 2016 | B2 |
D774654 | Anderson | Dec 2016 | S |
D778453 | Knaus et al. | Feb 2017 | S |
D779677 | Chen | Feb 2017 | S |
9561397 | Zaki | Feb 2017 | B2 |
D784544 | Dudkiewicz et al. | Apr 2017 | S |
D784546 | Gordon | Apr 2017 | S |
D784946 | Jun et al. | Apr 2017 | S |
D788056 | Choi et al. | May 2017 | S |
9656070 | Gozani et al. | May 2017 | B2 |
D789546 | Matfus et al. | Jun 2017 | S |
D789547 | Matfus et al. | Jun 2017 | S |
D791333 | Wilson | Jul 2017 | S |
D792363 | Kim et al. | Jul 2017 | S |
D794331 | Grote | Aug 2017 | S |
9731126 | Ferree et al. | Aug 2017 | B2 |
D801542 | Anderson | Oct 2017 | S |
D802780 | Hsu | Nov 2017 | S |
D806669 | Kangasmaa et al. | Jan 2018 | S |
D810843 | Karvandi | Feb 2018 | S |
D811729 | Bysshe | Mar 2018 | S |
D813405 | Ho | Mar 2018 | S |
D813407 | Chen | Mar 2018 | S |
D813408 | Chen | Mar 2018 | S |
D828569 | Mercuro | Sep 2018 | S |
D829182 | Li | Sep 2018 | S |
10076662 | Tuan | Sep 2018 | B2 |
D830565 | Xu | Oct 2018 | S |
D831017 | Choe et al. | Oct 2018 | S |
D831221 | Smith | Oct 2018 | S |
D831335 | Crease | Oct 2018 | S |
D832230 | Lee et al. | Oct 2018 | S |
D834719 | Theriot et al. | Nov 2018 | S |
D836788 | Peng | Dec 2018 | S |
20020010497 | Merfeld et al. | Jan 2002 | A1 |
20030023192 | Foxlin | Jan 2003 | A1 |
20030074037 | Moore et al. | Apr 2003 | A1 |
20030114892 | Nathan et al. | Jun 2003 | A1 |
20030208246 | Kotlik et al. | Nov 2003 | A1 |
20040122483 | Nathan et al. | Jun 2004 | A1 |
20050059903 | Izumi | Mar 2005 | A1 |
20050080463 | Stahmann et al. | Apr 2005 | A1 |
20060052788 | Thelen et al. | Mar 2006 | A1 |
20060085049 | Cory et al. | Apr 2006 | A1 |
20060089683 | Hagglof et al. | Apr 2006 | A1 |
20060095088 | De Ridder | May 2006 | A1 |
20060173507 | Mrva et al. | Aug 2006 | A1 |
20060190057 | Reese | Aug 2006 | A1 |
20070060922 | Dreyfuss | Mar 2007 | A1 |
20070276449 | Gunter et al. | Nov 2007 | A1 |
20080077192 | Harry et al. | Mar 2008 | A1 |
20080146980 | Rousso et al. | Jun 2008 | A1 |
20080147143 | Popovic et al. | Jun 2008 | A1 |
20080147146 | Wahlgren et al. | Jun 2008 | A1 |
20080312709 | Volpe et al. | Dec 2008 | A1 |
20090030476 | Hargrove | Jan 2009 | A1 |
20090082829 | Panken et al. | Mar 2009 | A1 |
20090112214 | Philippon et al. | Apr 2009 | A1 |
20090131993 | Rousso et al. | May 2009 | A1 |
20090240303 | Wahlstrand et al. | Sep 2009 | A1 |
20090264789 | Molnar et al. | Oct 2009 | A1 |
20090270947 | Stone et al. | Oct 2009 | A1 |
20090326604 | Tyler et al. | Dec 2009 | A1 |
20100004715 | Fahey | Jan 2010 | A1 |
20100042180 | Mueller et al. | Feb 2010 | A1 |
20100057149 | Fahey | Mar 2010 | A1 |
20100087903 | Van Herk et al. | Apr 2010 | A1 |
20100094103 | Kaplan et al. | Apr 2010 | A1 |
20100114257 | Torgerson | May 2010 | A1 |
20100131028 | Hsu et al. | May 2010 | A1 |
20100198124 | Bhugra | Aug 2010 | A1 |
20100217349 | Fahey | Aug 2010 | A1 |
20100241464 | Amigo et al. | Sep 2010 | A1 |
20110066209 | Bodlaender et al. | Mar 2011 | A1 |
20110224665 | Crosby et al. | Sep 2011 | A1 |
20110257468 | Oser et al. | Oct 2011 | A1 |
20110264171 | Torgerson | Oct 2011 | A1 |
20110276107 | Simon et al. | Nov 2011 | A1 |
20110282164 | Yang et al. | Nov 2011 | A1 |
20120010680 | Wei et al. | Jan 2012 | A1 |
20120108998 | Molnar et al. | May 2012 | A1 |
20130096641 | Strother et al. | Apr 2013 | A1 |
20130158627 | Gozani et al. | Jun 2013 | A1 |
20130217998 | Mahfouz et al. | Aug 2013 | A1 |
20140039450 | Green et al. | Feb 2014 | A1 |
20140057232 | Wetmore et al. | Feb 2014 | A1 |
20140081353 | Cook et al. | Mar 2014 | A1 |
20140107729 | Sumners et al. | Apr 2014 | A1 |
20140163444 | Ingvarsson et al. | Jun 2014 | A1 |
20140245791 | Proud et al. | Sep 2014 | A1 |
20140276549 | Osorio | Sep 2014 | A1 |
20140296934 | Gozani et al. | Oct 2014 | A1 |
20140296935 | Ferree et al. | Oct 2014 | A1 |
20140309709 | Gozani | Oct 2014 | A1 |
20140336730 | Simon et al. | Nov 2014 | A1 |
20140379045 | Rahimi et al. | Dec 2014 | A1 |
20150045853 | Alataris et al. | Feb 2015 | A1 |
20150174402 | Thomas et al. | Jun 2015 | A1 |
20150321000 | Rosenbluth et al. | Nov 2015 | A1 |
20150328467 | Demers et al. | Nov 2015 | A1 |
20150335288 | Toth et al. | Nov 2015 | A1 |
20160367823 | Cowan et al. | Dec 2016 | A1 |
20170209693 | An et al. | Jul 2017 | A1 |
20180177996 | Gozani et al. | Jun 2018 | A1 |
Number | Date | Country |
---|---|---|
1919139 | Feb 2007 | CN |
101626804 | Jan 2010 | CN |
102355847 | Feb 2012 | CN |
102740919 | Oct 2012 | CN |
102010052710 | May 2012 | DE |
61-171943 | Oct 1986 | JP |
4-347140 | Dec 1992 | JP |
9-117453 | May 1997 | JP |
2000-167067 | Jun 2000 | JP |
2005-34402 | Feb 2005 | JP |
2005-81068 | Mar 2005 | JP |
2006-68300 | Mar 2006 | JP |
418546 | Sep 2008 | JP |
WO 9742999 | Nov 1997 | WO |
WO 9964105 | Dec 1999 | WO |
WO 2003051453 | Jun 2003 | WO |
WO 2004078132 | Sep 2004 | WO |
WO 2007061746 | May 2007 | WO |
WO 2008079757 | Jul 2008 | WO |
WO 2008088985 | Jul 2008 | WO |
WO 2011075179 | Jun 2011 | WO |
WO 2011137193 | Nov 2011 | WO |
WO 2012116407 | Sep 2012 | WO |
Entry |
---|
Ancoli-Israel, S. et al., The Role of Actigraphy in the Study of Sleep and Circadian Rhythms, Sleep, 2003, 26(3), p. 342-392. |
Barbarisi, Manlio et al., Pregabalin and Transcutaneous Electrical Nerve Stimulation for Postherpetic Neuralgia Treatment, The Clinical Journal of Pain, Sep. 2010;26(7):567-572. |
Bjordal JM et al., Transcutaneous electrical nerve stimulation (TENS) can reduce postoperative analgesic consumption. A meta-analysis with assessment of optimal treatment parameters for postoperative pain, European Journal of Pain, 2003, vol. 7(2): 181-188. |
Bloodworth DM et al., Comparison of stochastic vs. conventional transcutaneous electrical stimulation for pain modulation in patients with electromyographically documented radiculopathy, American Journal of Physical Medicine & Rehabilitation, 2004, vol. 83(8): 584-591. |
Chandran P et al., Development of opioid tolerance with repeated transcutaneous electrical nerve stimulation administration, Pain, 2003, vol. 102: 195-201. |
Chen CC et al., A comparison of transcutaneous electrical nerve stimulation (TENS) at 3 and 80 pulses per second on cold-pressor pain in healthy human participants, Clinical Physiology and Functioning Imaging, 2010, vol. 30(4): 260-268. |
Chen CC et al., An investigation into the effects of frequency-modulated transcutaneous electrical nerve stimulation (TENS) on experimentally-induced pressure pain in healthy human participants, The Journal of Pain, 2009, vol. 10(10): 1029-1037. |
Chen CC et al., Differential frequency effects of strong nonpainful transcutaneous electrical nerve stimulation on experimentally induced ischemic pain in healthy human participants, The Clinical Journal of Pain, 2011, vol. 27(5): 434-441. |
Chen CC et al., Does the pulse frequency of transcutaneous electrical nerve stimulation (TENS) influence hypoalgesia? A systematic review of studies using experimental pain and healthy human participants, Physiotherapy, 2008, vol. 94: 11-20. |
Claydon LS et al., Dose-specific effects of transcutaneous electrical nerve stimulation on experimental pain, Clinical Journal of Pain, 2011, vol. 27(7): 635-647. |
Cole, R.J. et al., Automatic Sleep/Wake Identification From Wrist Activity, Sleep, 1992, 15(5), p. 461-469. |
Cruccu G. et al., EFNS guidelines on neurostimulation therapy for neuropathic pain, European Journal of Neurology, 2007, vol. 14: 952-970. |
Davies HTO et al., Diminishing returns or appropriate treatment strategy?—an analysis of short-term outcomes after pain clinic treatment, Pain, 1997, vol. 70: 203-208. |
Desantana JM et al., Effectiveness of transcutaneous electrical nerve stimulation for treatment of hyperalgesia and pain, Curr Rheumatol Rep. 2008, vol. 10(6): 492-499. |
Dubinsky RM et al., Assessment: Efficacy of transcutaneous electric nerve stimulation in the treatment of pain in neurologic disorders (an evidence-based review): Report of the therapeutics and technology assessment subcommittee of the american academy of neurology, Neurology, 2010, vol. 74: 173-176. |
Fary RE et al., Monophasic electrical stimulation produces high rates of adverse skin reactions in healthy subjects, Physiotherapy Theory and Practice, 2011, vol. 27(3): 246-251. |
Fishbain, David A. et al. Does Pain Mediate the Pain Interference with Sleep Problem in Chronic Pain? Findings from Studies for Management of Diabetic Peripheral Neuropathic Pain with Duloxetine, Journal of Pain Symptom Management, Dec. 2008;36(6):639-647. |
Fishbain, David A. et al., Transcutaneous Electrical Nerve Stimulation (TENS) Treatment Outcome in Long-Term Users, The Clinical Journal of Pain, Sep. 1996;12(3):201-214. |
Food and Drug Administration, Draft Guidance for Industry and Staff: Class II Special Controls Guidance Document: Transcutaneous Electrical Nerve Stimulator for Pain Relief, Apr. 5, 2010. |
Garrison DW et al., Decreased activity of spontaneous and noxiously evoked dorsal horn cells during transcutaneous electrical nerve stimulation (TENS), Pain, 1994, vol. 58: 309-315. |
Gilron, I. et al., Chronobiological Characteristics of Neuropathic Pain: Clinical Predictors of Diurnal Pain Rhythmicity, The Clinical Journal of Pain, 2013. |
Hori, T. et al., Skin Potential Activities and Their Regional Differences During Normal Sleep in Humans, The Japanese Journal of Physiology, 1970, vol. 20, p. 657-671. |
Jelinek HF et al., Electric pulse frequency and magnitude of perceived sensation during electrocutaneous forearm stimulation, Arch Phys Med Rehabil, 2010, vol. 91; 1372-1382. |
Jin DM et al., Effect of transcutaneous electrical nerve stimulation on symptomatic diabetic peripheral neuropathy: a meta-analysis of randomized controlled trials, Diabetes Research and Clinical Practice, 2010, vol. 89: 10-15. |
Johnson MI et al., Analgesic effects of different frequencies of transcutaneous electrical nerve stimulation on cold-induced pain in normal subjects, Pain, 1989, vol. 39: 231-236. |
Johnson MI et al., Transcutaneous Electrical Nerve Stimulation (TENS) and TENS-like devices: do they provide pain relief?, Pain Reviews, 2001, vol. 8: 7-44. |
Johnson MI et al., Transcutaneous electrical nerve stimulation for the management of painful conditions: focus on neuropathic pain, Expert Review of Neurotherapeutics, 2011, vol. 11(5): 735-753. |
Johnson; M.I. et al., An in-depth study of long-term users of transcutaneous electrical nerve stimulation (TENS). Implications for clinical use of TENS. Pain. Mar. 1991;44(3):221-229. |
Kaczmarek, Kurt A. et al., Electrotactile and Vibrotactile Displays for Sensory Substitution Systems. IEEE Trans. Biomed, Eng. Jan. 1991;38 (1):1-16. |
Kantor G et al., The effects of selected stimulus waveforms on pulse and phase characteristics at sensory and motor thresholds, Physical Therapy, 1994, vol. 74(10): 951-962. |
Keller, Thierry et al., Electrodes for transcutaneous (surface) electrical stimulation. J. Automatic Control, University of Belgrade. 2008;18(2):35-45. |
Koumans, A. J. R. et al., Electrodermal Levels and Fluctuations During Normal Sleep, Psychophysiology, 1968, 5(3), p. 300-306. |
Kripke, D.F. et al., Wrist Actigraphic Scoring for Sleep Laboratory Patients: Algorithm Development, Journal of Sleep Research, 2010, 19(4), p. 612-619. |
Law PPW et al., Optimal stimulation frequency of transcutaneous electrical nerve stimulation on people with knee osteoarthritis, J Rehabil Med, 2004, vol. 36: 220-225. |
Leonard G et al., Deciphering the role of endogenous opioids in high-frequency TENS using low and high doses of naloxone, Pain, 2010, vol. 151: 215-219. |
Levy et al., A comparison of two methods for measuring thermal thresholds in diabetic neuropathy, Journal of Neurology, Neurosurgery, and Psychiatry, 1989, vol. 52: 1072-1077. |
Lykken, D.T., Properties of Electrodes Used in Electrodermal Measurement. J. Comp. Physiol. Psychol. Oct. 1959;52:629-634. |
Lykken, D.T., Square-Wave Analysis of Skin Impedance. Psychophysiology. Sep. 1970;7(2):262-275. |
Melzack R et al., Pain mechanisms: A New Theory, Science, 1965, vol. 150(3699): 971-979. |
Moran F et al., Hypoalgesia in response to transcutaneous electrical nerve stimulation (TENS) depends on stimulation intensity, The Journal of Pain, 2011, vol. 12(8): 929-935. |
Oosterhof, Jan et al., Outcome of transcutaneous electrical nerve stimulation in chronic pain: short-term results of a double-blind, randomised, placebo-controlled trial. J. Headache Pain. Sep. 2006;7(4):196-205. |
Ocsterhof, Jan et al., The long-term outcome of transcutaneous electrical nerve stimulation in the treatment for patients with chronic pain: a randomized, placebo-controlled trial. Pain Pract. Sep. 2012;12(7):513-522. |
Pantaleao MA et al., Adjusting pulse amplitude during transcutaneous electrical nerve stimulation (TENS) application produces greater hypoalgesia, The Journal of Pain, 2011, vol. 12(5): 581-590. |
Paquet, J. et al., Wake Detection Capacity of Actigraphy During Sleep, Sleep, 2007, 30(10), p. 1362-1369. |
Pieber K et al., Electrotherapy for the treatment of painful diabetic peripheral neuropathy: a review, Journal of Rehabilitation Medicine, 2010, vol. 42: 289-295. |
Raskin, J. et al., A Double-Blind, Randomized Multicenter Trial Comparing Duloxetine with Placebo in the Management of Diabetic Peripheral Neuropathic Pain, Pain Medicine, 2005, 6(5), p. 346-356. |
Sadeh, A., The Role and Validity of Actigraphy in Sleep Medicine: An Update, Sleep Medicine Reviews, 2011, vol. 15, p. 259-267. |
Sadosky, A. et al., Burden of Illness Associated with Painful Diabetic Peripheral Neuropathy Among Adults Seeking Treatment in the US: Results from a Retrospective Chart Review and Cross-Sectional Survey, Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 2013, vol. 6. p. 79-92. |
Scherder, E. J. A. et al., Transcutaneous Electrical Nerve Stimulation (TENS) Improves the Rest-Activity Rhythm in Midstage Alzheimer's Disease, Behavioral Brain Research, 1999, vol. 101, p. 105-107. |
Tryon, W. W., Issues of Validity in Actigraphic Sleep Assessment, Sleep, 2004, 27(1), p. 158-165. |
Tsai, Y. et al., Impact of Subjective Sleep Quality on Glycemic Control in Type 2 Diabetes Mellitus, Family Practice, 2012, vol. 29, p. 30-35. |
Van Boxtel, A., Skin resistance during square-wave electrical pulses of 1 to 10 mA. Med. Biol. Eng. Comput. Nov. 1977;15(6):679-687. |
Van Someren, E. J. W. et al., Gravitational Artefact in Frequency Spectra of Movement Acceleration: Implications for Actigraphy in Young and Elderly Subjects, Journal of Neuroscience Methods, 1996, vol. 65, p. 55-62. |
Webster, J. B. et al., An Activity-Based Sleep Monitor System for Ambulatory Use, Sleep, 1982, 5(4), p. 389-399. |
Zelman, D. C. et al., Sleep Impairment in Patients With Painful Diabetic Peripheral Neuropathy, The Clinical Journal of Pain, 2006, 22(8), p. 681-685. |
Aurora, R. et al., The Treatment of Restless Legs Syndrome and Periodic Limb Movement Disorder in Adults—An Update for 2012: Practice Parameters with an Evidence-Based Systematic Review and Meta-Analyses, Sleep, 2012, vol. 35, No. 8, p. 1039-1062. |
Bonnet, M. et al., Recording and Scoring Leg Movements, Sleep, 1993, vol. 16, No. 8, p. 748-759. |
Boyle, J. et al., Randomized, Placebo-Controlled Comparison of Amitriptyline, Duloxeline, and Pregabalin in Patients With Chronic Diabetic Peripheral Neuropathic Pain, Diabetes Care, 2012, vol. 35, p. 2451-2458. |
Kovacevic-Ristanovic, R. et al., Nonpharmacologic Treatment of Periodic Leg Movements in Sleep, Arch. Phys. Med. Rehabil., 1991, vol. 72, p. 385-389. |
Lopes, L. et al., Restless Legs Syndrome and Quality of Sleep in Type 2 Diabetes, Diabetes Care, 2005, vol. 28, No. 11, p. 2633-2636. |
Nightingale, S., The neuropathic pain market. Nature Reviews, 2012, vol. 11, p. 101-102. |
Zucconi, M. et al., The official World Association of Sleep Medicine (WASM) standards for recording and scoring periodic leg movements in sleep (PLMS) and wakefulness (PLMW) developed in collaboration with a task force from the International Restless Legs Syndrome Study Group (IRLSSG), Sleep Medicine, 2006, vol. 7, p. 175-183. |
Sheridan et al., Some Factors Influencing the Threshold of the Electrocutaneous Stimulus, Perceptual and Motor Skills, 1966, vol. 22, pp. 647-654. |
Susi, M. et al., Motion Mode Recognition and Step Detection Algorithms for Mobile Phone Users, Sensors, vol. 13, 2013, pp. 1539-1562. |
Amazon, “Quell 2.0 Wearable Pain Relief Technology”, Sep. 15, 2018. http://www.amazon.com/Quell-Wearable-Pain-Relief-Technology/dp/B07DHW2MJJ/ref=cm_cr_arp_d_product_top?ie=UTF8. Shown on p. 1. (Year: 2018). |
Amazon, “Quell Wearable Pain Relief Technology Starter Kit”, Oct. 18, 2017. http://www.amazon.com/Quell-Wearable-Relief Technology-Starter/dp/B075YVCLZT/ref=cm_cr_arp_d_product_top?ie=UTF8. Shown on p. 1. (Year: 2017). |
Number | Date | Country | |
---|---|---|---|
20180015285 A1 | Jan 2018 | US | |
20190001130 A9 | Jan 2019 | US |
Number | Date | Country | |
---|---|---|---|
62361698 | Jul 2016 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 14253628 | Apr 2014 | US |
Child | 15648173 | US |