This invention relates in general to technique for monitoring the effectiveness of medication taken to treat Attention Deficit Hyperactivity Disorder (ADHD) and more particularly to a technique and apparatus for measuring and objectively analyzing an individual's peripheral temperature variability to determine values indicative of the level of manifestation of ADHD.
ADHD is the most common neurobehavioral disorder of childhood as well as among the most prevalent health conditions affecting school-aged children. Between 4% and 12% of school age children (several millions) are affected. $3 billion is spent annually on behalf of students with ADHD. Moreover, in the general population, 9.2% of males and 2.9% of females are found to have behavior consistent with ADHD. Upwards of 10 million adults may be affected.
ADHD is presently a difficult disorder to diagnose. The core symptoms of ADHD in children include inattention, hyperactivity, and impulsivity. ADHD children may experience significant functional problems, such as school difficulties, academic underachievement, poor relationships with family and peers, and low self-esteem. Adults with ADHD often have a history of losing jobs, impulsive actions, substance abuse, and broken marriages. ADHD often goes undiagnosed if not caught at an early age and affects many adults who may not be aware of the condition. ADHD has many look-alike causes (family situations, motivations) and co-morbid conditions (depression, anxiety, and learning disabilities) are common.
Diagnosis of ADHD currently involves a process of elimination using written and verbal assessment instruments. However, there is no one objective, independently validated test for ADHD. Various objective techniques have been proposed but have not yet attained widespread acceptance. These include:
1. The eye problem called convergence insufficiency was found to be three times more common in children with ADHD than in other children by University of California, San Diego researchers.
2. Infrared tracking to measure difficult-to-detect movements of children during attention tests combined with functional MRI imaging of the brain were used by psychiatrists at McLean Hospital in Belmont, Mass. to diagnose ADHD in a small group of children (Nature Medicine, Vol. 6, No. 4, April 2000, Pages 470–473).
3. Techniques based on EEG biofeedback for the diagnoses and treatment of ADHD are described by Lubar (Biofeedback and Self-Regulation, Vol. 16, No. 3, 1991, Pages 201–225).
4. U.S. Pat. No. 6,097,980, issued Aug. 1, 2000, inventor Monastra et al, discloses a quantitative electroencephalographic process assessing ADHD.
5. U.S. Pat. No. 5,913,310, issued Jun. 22, 1999, inventor Brown, discloses a video game for the diagnosis and treatment of ADHD.
6. U.S. Pat. No. 5,918,603, issued Jul. 6, 1999, inventor Brown, discloses a video game for the diagnosis and treatment of ADHD.
7. U.S. Pat. No. 5,940,801, issued Aug. 17, 1999, inventor Brown, discloses a microprocessor such as a video game for the diagnosis and treatment of ADHD.
8. U.S. Pat. No. 5,377,100, issued Dec. 27, 1994, inventors Pope et al., discloses a method of using a video game coupled with brain wave detection to treat patients with ADHD.
9. Dr. Albert Rizzo of the integrated Media Systems Center of the University of Southern California has used Virtual Reality techniques for the detection and treatment of ADHD.
10. U.S. Pat. No. 6,053,739, inventors Stewart et al., discloses a method of using a visual display, colored visual word targets and colored visual response targets to administer an attention performance test.
U.S. Pat. No. 5,377,100, issued Dec. 27, 1994, inventors Patton et al., discloses a system and for managing the psychological state of an individual using images.
U.S. Pat. No. 6,117,075 Barnea discloses a method of measuring the depth of anesthesia by detecting the suppression of peripheral temperature variability.
There are several clinical biofeedback and physiologic monitoring systems (e.g. Multi Trace, Bio Integrator). These systems are used by professional clinicians. Although skin temperature spectral characteristics have been shown to indicate stress-related changes of peripheral vasomotor activity in normal subjects, there has been no disclosure of use of variations in skin-temperature response to assist in diagnosing ADHD. (See: Biofeedback and Self-Regulation, Vol. 20, No. 4, 1995).
As stated above, the primary method for diagnosing ADHD is the use of a bank of written and verbal assessment instruments designed to assess the children for behavioral indicators of criteria established by American Medical Association (AMA) as described in the Diagnostic and Statistics manual—IV (DSM-IV). Psychiatrists, psychologists, school psychologists and other licensed practitioners administer these assessment instruments. In some cases those individuals who meet DSM-IV criteria for ADHD diagnosis are prescribed a drug such as Ritalin. Behavioral observations of the patient while on Ritalin are conducted to assess the impact of prescribed medication. However, clearly established criteria for evaluating the impact of specific medications e.g., Ritalin and specific dosages are lacking. It would be advantageous for physicians to have access to clearly established physiologic criteria, which could be measured, to determine if a specific medication at a specific dosage effectively addressed the underlying physiologic parameter, which was indicative of ADHD.
There is thus a need for a simple, inexpensive, and reliable objective technique for determining the effectiveness of the medication and appropriate dosage taken to counteract ADHD by an individual who has ADHD.
According to the present invention, there is provided a solution to the problems discussed above.
According to a feature of the present invention, there is provided a method for determining the appropriate dosage of a medication to treat Attention Deficit Hyperactivity Disorder (ADHD) in an individual who has ADHD comprising:
(a) sampling the peripheral skin temperature of left and right like extremities of an individual during a predetermined time interval when the subject is in a sensory deprived state to provide respective left and right sampled peripheral skin temperature data;
(b) a first processing of at least one of said left and right sampled peripheral skin temperature data providing conversion to the frequency domain to derive a first spectral signature having magnitude values;
(c) a second processing of both said left and right sampled peripheral skin temperature data to derive temporally correlated differential data;
(d) said second processing further filtering said differential data with a high pass filter to produce filtered differential data with near d, c, components removed;
(e) said second processing lastly providing conversion to the frequency domain of said filtered differential data to derive a second spectral signature having magnitude values;
(f) a third processing of the said first spectral signature for the determination of the level of manifestation of ADHD by comparison to a predetermined first threshold value;
(g) a fourth processing of the said second spectral signature for the determination of the level of manifestation of ADHD by comparison to a predetermined threshold value; and
(h) a fifth processing wherein an assessment of the bi-modal quality of the results of the third and fourth processing is made, to provide a final determination of one of the following three possibilities:
(i) a various level of dosage change;
(ii) dosage level is adequate,
(iii) there is noise in the data.
The invention has the following advantages.
1. A device and technique for objectively determining the effectiveness of the medication and appropriate dosage taken to counteract ADHD by an individual who has ADHD which is simple, inexpensive and reliable.
a and 3b are block diagrams of portions of a system incorporating the present invention.
According to the present invention, it has been found that signatures of ADHD are hidden in fluctuation of the temperature of the skin as measured at the extremities such as at the fingertips. In general, as an individual's stress level increases the peripheral vasculature constricts and often the person's blood pressure increases. As the blood vessels in the body constrict, blood flow is restricted. This is most easily monitored in the extremities such as the fingers, because the blood vessels in the extremities are small and very responsive to Sympathetic Nervous System (SNS) innervations. A direct result of decreased blood flow to the blood vessels in the extremities is a decrease in the peripheral temperature of the extremities. Conversely, as an individual's stress level decreases and relaxation occurs, the blood vessels expand, allowing blood to flow in a less restricted manner. As the blood flow to the vessels in the extremities increases the peripheral temperature of the extremities increases. It is suspected that when a subject with ADHD is subjected to sensory deprivation such as being made to look at a blank screen or an obscured image for a period of time in an inactive state, the lack of stimulation increases and there tends to be a shift in the subject's physiologic reactivity indicative of an increase in their stress level. As their stress level increases their blood vessels contract and the peripheral temperature of their extremities decreases. Biofeedback practitioners have long used measurement of hand temperature to help subjects manage their physiology by controlling blood flow to the extremities. The literature reports that reduced blood flow to the brain is frequently found in patients with ADHD.
In addition to peripheral skin temperature and peripheral skin temperature variability there are other known physiologic measures which are known (or potential) indicators of stress such as; bilateral temperature variability, heart rate, heart rate variability, muscle tension (excessive and chronic, measured via surface electromyography—sEMG), bilateral muscle tension imbalance, galvanic skin response (i.e. electro dermal response—EDR), eye saccades, blood oxygen (SpO2), salivary IGA, electroencephalography (EEG), peripheral blood flow (measured via photoplethismography—PPG), and peripheral blood flow variability (PPG).
As shown in
As shown in
In a further embodiment, a slot 118 is provided to accept a memory card 119 to allow the transport of the recorded temperature data. In these embodiments, the data processing and analysis is done at a different location, for example at a computer, a PDA device, or through the Internet. In another embodiment, the electronics to do the data processing and analysis is contained in the temperature recording module, with the results transported by any of the aforesaid means. The display 26 may also show the result, in addition to indicating that fingertip temperatures are being sensed correctly prior to the start of a session. In this self-contained configuration, the system may be made upgradeable by providing bi-directionality across the data transport path.
In
First Processing
In the preferred embodiment of the present invention, a first processing is next carried out on these data. As shown in
Now further referring to
FFT(fm)=A(fm)+B(fm)i
where i is the √{square root over (−1)}. The Phase Φ(fm) is then found from the equation
and the Magnitude M(fm) from
Ml(fm)=√{square root over (B(fm)2+A(fm)2)}{square root over (B(fm)2+A(fm)2)} (1.1)
In the equations 1.0 and 1.1 the subscript l refers to the fact that a separate signal is extracted for each hand so the subscript is l for data extracted from the left-hand data and r for data from the right hand.
Raw Data
The raw data Tk,l(t) is the temperature taken from hand l at a fingertip 16 as shown in
Referring again to
Windows
The data for each session were divided into a series of windows (block 43) prior to performing the Fourier Transform operation. Call the window width w. In this analysis, the window width was 64 seconds and there were 10 windows spaced at 50-second intervals (the windows overlap) across the 600 sec baseline spanning the range of 100–500 sec, other values of w can be used. The window number in a session is referred to with the letter j. For each window a FFT algorithm calculates the Fourier Transform F(f). The Magnitude and Phase of this transform are defined as given above.
In block 46 the range of magnitude variation during a window is calculated using equation (1.2) below where fmax and fmin are the frequencies where the Magnitude is the greatest and the least respectively (note the dc component at frequency zero is excluded).
Mrange=[M(fmax)−M(fmin)] (1.2)
In a further embodiment of this method, other statistics from a Fourier Transform, calculated from the quantities denoted above as A(fm), B(fm), θ(fm), and M (fm) may be used. In addition to using Fourier Transforms, another embodiment may use statistics derived from a Wavelet transform of data or other filtering of the data (as in Strang, G. and Nguyen, T. (1996), Wavelets and Filter Banks, Wellesley-Cambridge Press, Wellesley, Mass.).
Aggregation of Samples
During this first processing, windowing the data for conversion to the frequency domain results in multiple first spectral signatures like those shown in
And the corresponding variance is:
Combining these session means and variances over both hands and all the sessions s that a subject attended gives an aggregated mean μ and aggregated variance.
Further embodiments of this aggregation step of the first processing include using the data from only one hand—either the left hand, the right hand, or the dominant hand (and if the subject is ambidextrous, the dominant hand would be defined as the average of both hands). In addition, future embodiments may not require averaging of several sessions, but selecting only one session for use or using a weighted combination of each session's results.
Diagnostic Indicators
Referring again to
When the subject's measured aggregation statistic Θm (from equation 2.2 or 2.3) block 47 is less than the group threshold θg− block 49, the test 48 indicates the subject has ADHD. When the measured aggregation Θm statistic is greater than the predetermined threshold θg, the test indicates no manifestation of ADHD-block 50 and no medication is required-block 51. The same threshold θg may be used for all subjects or θg may have a value that is different for different groups based on gender or age.
Determination of Proper Dosage
Now referring to
Dosage=100x(θg−Θm−1)+100x gender
where the dosage is in milligrams of a drug, and where gender is coded as 0 if the patient is female and 1 if the patient is male. For example, if θg=10 and Θm=8, and the patient is male, the example formula would call for a dosage of 100x(10−8−1)+100x1=200 milligrams of the drug.
Medication Effectiveness Indicator
If the prescribed medication is effective in correcting the ADHD, then the measured physiologic diagnostic indicator Θm (as defined by equation 2.2 or 2.3) would be expected to come within the normal range and exceed θg during the time the patient is medicated
Thus, to determine if the dosage is effective, the patient will be re-tested according to the following procedure as illustrated in
Because a patient's physiology can change over time, the effective dosage may change over time as well. Thus, the patient needs to be monitored during the treatment period in accordance with the best medical practices. One such monitoring scheme, which should be followed during the entire time the patient is taking the drug, is to periodically re-test the patient. The interval between these periodic tests can for example, be one month to one year. The monitoring procedure involves repeating blocks 70–78. In one embodiment of the invention, the initial dosage found-block 78 could be replaced with an enhancement in which, if Θm exceeds θg by a large amount, the dosage is decreased, while if Θm exceeds θg by a small amount, then the proper dosage has been found
Complementary Analysis Method
In the preferred embodiment of the present invention, a second processing of the data allows the assessment of the bi-modality of the spectral energy of peripheral temperature variability where, for example, when ADHD is manifesting, the just described first processing determines a decrease of spectral energy below around 0.005 Hz, and the second processing next described determines an increase in bilaterally differential spectral energy 0.03 Hz. The opposite bi-modality should be seen with adequate medication.
Referring to
As there may be differences in software to perform this transform, the application used is identified here as the DaDisp™ application by DSP Development Corporation.
The resultant high-passed differential data are then passed through a Fast Fourier Transform (also by DaDisp™) 104, to derive the spectral signature, which is then compared 108 against a pre-determined norm 106, generating result 110 of
Thusly, similar to the analysis method of the first processing, the just described second processing provides a measurement means for medication effectiveness, that is, the magnitude of a final spectral signature. But with two differences: firstly, the portion of the spectrum of interest is centered around 0.03 Hz., and secondly, the magnitude of the spectral signature decreases in a proportion to the effectiveness of the medication.
It is therefore concluded here, considering the aforesaid determination, that very slow peripheral temperature variability is not simply suppressed in ADHD manifestation, but rather, moves upward in frequency, and becomes markedly bilaterally differential in nature.
The mechanism for this ADHD manifestation is thought to be the lessening of the slower, common control of the left and right peripheral temperatures by the autonomic nervous system, resulting in the control of temperature at said periphery being more localized and therefore less correlated to each other.
Multiplicity of Tests
A well known statistical principle is that the variability of the average of multiple tests is less than the variability of one test. Therefore, an advantage of effective, additional, concurrent testing, e.g. the combined analyses of the same session data, is increased accuracy.
Noise Detection
A key advantage of the present invention that combines the first processing and the just described second analysis processing is the ability to distinguish external noise from true physiological function. External noise will manifest as increased spectral content, which can occur anywhere in the spectrum, including within the regions of interest. It may be anywhere from broadband to very frequency-specific. Such noise is usually difficult to discern unless the specific frequency or bandwidth is known, which is not the case with such measurements.
The present invention provides a means for noise detection due to the nature of vasomotor activity. Peripheral temperatures are ultimately controlled in all cases, thereby producing the same total spectral energy on average. The present invention provides complimentary tests of this feature of physiology, that if the magnitude of energy is less in one spectral region, the case in the first processing when ADHD is manifesting, the magnitude of energy is greater in the other spectral region, the case in the second processing, The matched opposites of these results indicate that the subject is receiving adequate medication. This bi-modal spectral characteristic will not be seen with noise since it can only be additive. Noise in the data is thereby identifiable. This is accomplished at block 112 of
According to the present invention then, the now described fist and second processing result in the following possible test outcomes:
The invention has been described in detail with particular reference to certain preferred embodiments thereof, but it will be understood that further study could indicate refinements and optimizations, ad that such variations and modifications can be effected within the spirit and scope of the invention.
This application is a continuation of and claims priority from U.S. Ser. No. 10/092,284, filed Mar. 6, 2002, now U.S. Pat. No. 6,726,624.
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Number | Date | Country | |
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20050025704 A1 | Feb 2005 | US |
Number | Date | Country | |
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Parent | 10092284 | Mar 2002 | US |
Child | 10832824 | US |