Sensitivity and specificity of a portable system measuring postural tremor

Neurotoxicology and Teratology, Vol. 19, No. 2, pp. 95-104,1997 Copyright 0 1997 Elsevier Science Inc. Printkdk the USA. All rights reserved

0892.0362/97$17.00+ .OO

PIISO892-0362(96)00179-l

Sensitivity and Specificity of a Portable System Measuring Postural Tremor RODERICK

EDWARDS

AND

ANNE

BEUTER

Dkpartement de Kinanthropologie, Universit6 du Qutbec LiMont&al, C.P. 8888, succ. Centre-ville, Montrdal, PQ, Canada H3C 3P8

Received

2 May 1996; Accepted

31 July 1996

EDWARDS, R. AND A. BEUTER. Sensitivity and specificity of a portable system measuring postural tremor. NEUROTOXICOL TERATOL 19(2) 95-104, 1997.-A portable, accelerometric system measuring tremor was evaluated. That is, the validity and consistency of measurements as well as its ability to discriminate pathologic from physiological tremor were investigated. Control subjects and patients with Parkinson’s disease were tested with this portable system and with an independent system that gave precise displacement data using lasers. It was found that amplitude of postural tremor as measured by the two systems differed significantly, but further investigation revealed that this difference was due 1) to the difference between amplitude of acceleration and amplitude of displacement, and 2) to changes in tremor over the time between tests, rather than to any inaccuracy or unreliability in the portable system. The other characteristics of tremor reported by the portable system were also valid and reasonably reliable in test-retest experiments, with the exception of the “harmonic index,” which proved less stable. Most of the reported characteristics were distributed differently for the control group and for the patients with Parkinson’s disease, but the large overlaps between distributions would make diagnosis difficult when tremor is not very pronounced. These results suggest that until better discriminating measures of tremor are available, tremor tests should be repeated and combined with other tests of motor function. 0 1997 Elsevier Science Inc.

Tremor quantification

Neurological deficits

Portable system

sway. Traditionally,

neuromotor test batteries have included subsets of these items. Among these tests, tremor is probably one of the most difficult movements to record and analyse adequately (3). This is an especially important issue because it appears that tremor is relatively vulnerable to neurotoxic influences but the recorded changes are usually subtle and the variability in the normal population is high. Tremor is defined as involuntary and continuous oscillatory movements of body parts such as extremities, jaws, eyes, or head that are normally present in healthy subjects (i.e., physiological tremor) but may change as a function of fear, anxiety, cold, anger, or hypoglycaemia (i.e., enhanced physiological tremor) (16). Sometimes enhanced physiological tremor is perfectly normal (it is basically physiological tremor with a larger amplitude); however, at other times it may reflect metabolic disturbances or pathologies of the nervous system (8). Like all movement abnormalities, physiological tremor tends to fluctuate over time in a significant way that makes it

BEHAVIORAL testing of occupational populations based on neuropsychology and experimental psychology started in the 1960s and has continuously evolved since. For example, the number of tests has considerably expanded and tests have

become computerized (1). Recently researchers have become aware that subtle changes in neuromotor control might represent a pathognomonic sign of neurotoxicity. As a result, a few valid and reliable neuromotor test batteries have been developed. One of them, composed of the Tremor Analysis Test System and the Coordination Ability Test System developed in Denmark in 1992 by Danish Product Development (DPD) is now available commercially to quantify exposure to neurotoxic agents such as metals, solvents, or pesticides. A sample of 61 normal subjects was tested with the Tremor Analysis Test System for standardization by Dr. Sigurd Mikkelsen at the Clinic of Occupational Health, Copenhagen County Hospital [(4) p. 311. Typical items included in neuromotor evaluation include measures of reaction time, finger tapping, rapid alternating movements, tremor, hand dexterity, and postural

-

Kequests tor reprints should be addressed to Anne Beuter, DCpartement de Kinanthropologie, succ. Centre-ville, Montrtal, PQ, Canada H3C 3P8. Fax: (514) 987-6616.

9.5

UniversitC du QuCbec B MontrCal, C.P. 8888,

EDWARDS

96 harder to classify in normal and pathological types (8,9,11,13). Authors have attempted to classify tremor by aetiology, by behavioral characteristics, by frequency, by electromyography, by pharmacological response, or by origin (i.e., central vs. peripheral). Other tremors defined as psychogenic (14) psychotic (lo), and orthostatic (i.e., rapid, irregular, and asynchronous) (18) are usually excluded from these classifications (8). These last authors indicate that today no single classification scheme is available to be used diagnostically. One additional difficulty is that other movement abnormalities such as clonus. chorea, or tics may also have, like tremor. an oscillatory nature. Tools and methodologies used to quantify and analyse tremor generally lack standardisation and it is not unusual to find completely opposite conclusions in studies dealing with a similar problem (3). We decided to select a pathology characterized by relatively well-known symptoms and to examine critically the ability of a typical test to detect differences in the subjects’ performance. Therefore, the purpose of this study was to determine the sensitivity (detecting small differences in tremor), specificity (detecting differences specific to a particular condition), and consistency of a simple, portable accelerometer system (the DPD system). First. tremor amplitude in patients with Parkinson’s disease and in healthy normal control subjects was quantified using precise displacement data from a laser-based system (LB). Second, all subjects were classified into two groups (i.e.. low-tremor amplitude and high-tremor amplitude groups) and tested using the DPD system. Third. the five characteristics calculated by the DPD system were compared between high- and low-tremor amplitude groups and between groups defined by a neurological assessment of presence or absence of Parkinson’s disease symptoms. Finally. validity was tested by a simultaneous recording of tremor by the two systems and consistency was checked by testing another group of subjects twice using the DPD system.

The Danish Product Development

AND

BEUTER

Tremor Test (DPD)

This tremor test has been developed by Danish Product Development (Fig. 1). It measures postural tremor successively in each hand during about 8.2 s while subjects look at a light stylus that they hold horizontally 10 cm away from their navel. The stylus is sensitive in a plane perpendicular to the tube axis and is individually calibrated with a calibration file. Two axis microaccelerometers embedded in the tip of the stylus measure accelerations in orthogonal directions. Samples arc taken at 500 Hz but are subsampled at 31.25 Hz after being put through a low-pass filter (5). The raw accelerations, after calibration, are reported to be accurate to within l-10% (standard deviation) across the frequency range used [(4). p. 201. The stylus is connected to a personal computer via a datalogger. Fourier transforms are calculated from the two time ser-ies and combined by a Pythagorean sum to give a single power spectrum. Recorded data (time series and power spectrum) and group statistics can be visualized immediately and power spectrum data can be exported in ASCII format for further analysis. Measures derived from acceleration data are based on the Fourier power spectrum. which gives a power distribution of the data in the frequency domain. It is composed of 1 I6 discrete values in the 0.9-15 Hz range. each approximately 0.12 Hz apart. This spectrum is supposed to react to “deviant” tremor patterns.

Fifty-four subjects were included in the primary study, 21 of them in the early stages (I and II) (12) of Parkinson’s disease. Control subjects were selected in the same age range. All the subjects were assessed by a neurologist on the same day as the tremor recordings were taken. The clinical examination revealed that all of the control subjects were free of neurological disorders except one who had a moderate rssential tremor. and two others who were assessed as having mild essential tremor. These last two. however, had tremor indistinguishable from normal tremor in our recordings. All sub,jects performed the two types of test (DPD and LB) with each hand. The LB test was done twice in succession for each hand. with a 30-s tracking task between the two trials.

Limitatiot2s Tremor was measured using the DPD and LB systems within a period of about 1 h so some differences may be present due to changes in conditions over this time (e.g.. fatigue, anxiety). Changes in amplitude were sometimes observed visibly over periods of a few minutes. Also, patients were under medication and this may have contributed to hide some of the symptoms. but it is well known that tnedications have a limited effect on tremor (7). To what extent medications alter tremor characteristics aside from amplitude is unknown.

FIG.

I. The Danish Product

Development

Tremor

Test

POSTURAL

TREMOR

The specific parameters

MEASURING examined

(4) are as follows:

1. Tremor intensity (I) is the RMS of acceleration recorded in the 0.9-15 Hz band during the 8.192-s test period and is expressed in m/s*. This is usually called “amplitude” in the literature and we use the latter term throughout. 2. Centre Frequency (F50) is the median frequency of the acceleration in the 0.9-15 Hz band during the 8.2-s test period: 50% of the area under the spectrum is at frequencies above the centre frequency and 50% is below. Units are Hz or s I. Based on a test performed by DPD on 61 control subjects, the normal human means for left and right hand are 7.5 and 7.2 Hz, respectively. 3. Standard Deviation of Centre Frequency (SFSO) indicates the degree of irregularity of the tremor. Sixty-eight percent of the area under the spectrum lies within 1 SD of the centre frequency. A simple rhythmic tremor has a small SF50 indicating that most of the area is within a narrow frequency band. Based on a test performed by DPD on control subjects, the normal human means for left and right hand are 3.8 and 3.5 Hz, respectively. 4. Harmonic Index (HI) compares the tremor spectrum with that of a single harmonic oscillation, which has a HI = 1.OO. A tremor composed of a few dominating frequencies has a high HI. It is defined as the area above the normalized spectrum (i.e., the highest peak is set to a power of I) between 0.Y and 14.9 Hz and below a power of 1. Based on a test performed by DPD on control subjects, normal tremor has a HI centered around 0.88, reflecting its irregular character, but values up to 0.95 are not unusual. 5. Tremor Index (TI) is a single measure incorporating the four previous measures. Any value deviating significantly from the norm will contribute a smaller than usual amount to the TI. The method of calculation is as follows: Let the recorded value for each of the four characteristics be denoted K,. Let the normal human mean and SD for each characteristic be denoted hl, and S,. respectively. Then the TI is given by TI = F c(ai

97

SYSTEM

exp (- I (K, - MI)/S, I).

where I;is a scaling factor to make the mean Tl of the test sample of normal human subjects equal 100 and the ai are l/6 for all except amplitude, for which a, is 113. (There is also a fifth component. SHI, a measure of dispersion of the Harmonic Index. which was used in previous versions of the DPD system but is no longer reported. though it is still apparently used in the calculation of the TI).

Past studies have shown that a LB system (2) measuring displacement can be used to record human tremor with high precision. In the present study. the LB system was used to quantify the amplitude of postural tremor and to classify the subjects into two groups: one group of subjects whose tremor was larger (detrended RMS > 0.17 mm) and the other group whose tremor was smaller (detrended RMS < 0. I7 mm). The LB system is placed at a fixed distance from the finger tip. This system uses analog output sensors based on optical triangulation range measurement. The laser beam emitted from the light-emitting element (semiconductor laser) passes through the projector lens to a target. A part of the diffusereflected laser light passes through the receiver lens to a spot on the position-sensitive device. The position of the light spot varies actor-ding to the detected distance. The change in out-

put currents caused by a deflection of the light spot OIIthe position-sensitive device is used to determine distance. Because this deflection is independent of the volume of the incident light. a stable distance measurement can be made. Proctdures

Used with the Laser-Bused

System (LB)

The subject is comfortably seated in a chair with the elbow joints flexed at 90” and resting on a foam-padded support. The subject’s forearm is lying pronated on the padded support. The index finger is extended while the remaining fingers of the tested hand rest in a semiflexed position on a specially molded soft support. Interphalangeal joints of the index are blocked by a light splint (-7 g) and vertical displacement of the index at the metacarpo-phalangeal joint is measured at the center of the finger nail (-10 cm from the joint). Visual feedback is presented on an oscilloscope screen placed 80 cm in front of the subject. A line corresponding to the finger position is displayed on the screen and subjects arc asked to try to keep this line on a fixed reference line. The analog signals recorded from the laser are sampled at 200 H7 for 30 s using an acquisition system (Experimenter’s Workbench. DataWave Technologies, Longmont, CO). The displacement data from the lasers were detrended by subtracting cubic polynomials fitted to 200 points (which corresponds to 1 s) every 0.5 s, over five 1024-point segments. A gradual transition was made (by linear combination) between the overlapping parts of successive cubits. This was intended to capture the shape of the curve smoothly. The magnitudes of the five segments were then averaged in the Fourier domain and tremor amplitude was calculated as the RMS of displacement of the KY-15 Hz component of the detrended and averaged signal. This method was used to remove the low-frequency component of the signal (due to drift. breathing, and hear-tbeat). and was preferred to a low-pass filter because it also removed the contribution of these factors to higher frequency parts of the spectrum (due to the effect known as “leakage”). Though curve fitting is usually avoided in spectral analysis. as it can create small artifacts in the spectrum. here we are only calculating amplitude of tremor (essentially a time domain characteristic). RtSC!LIS

The distribution of tremor amplitudes recorded with the LB system for the 216 trials (54 subjects X 2 hands X 2 trials) had a bimodal form (Fig. 2). with a large group below about 0.17 mm and a smaller group with a mode above this value. This was used as a criterion for dividing the trials into lowand high-amplitude groups. A particular hand of a particular subject was deemed to belong to the high-amplitude group if either of the trials for that hand did. This gave 12 cases (subject. hand) in the high-amplitude group and 96 cases in the low-amplitude group for subsequent analysis using the DPD system. Note that the high-amplitude group includes four cases (out of 66) from the control group and the low-amplitudc group includes 34 cases (out of 42) from the patient group (including the nonaffected hand in particular).

Kesults for the five characteristics reported by the DPD system for each hand of each subject in the two groups (as defined by the LB system) arc summarized in Table 1 (means

98

EDWARDS

AND

I

I

I

I

I

I

-5

-4

-3

-2

-1

0

BEUTER

Log intensity (mm)

FIG. 2. Histogram of LB tremor amplitude from detrended displacement data (54 subjects x 2 hands x 2 trials). The arrow divides the high- and low-amplitude groups. (Note that the high-amplitude group includes trials from control subjects and the low-amplitude group includes trials from patients).

and SDS). Figure 3 gives a histogram of DPD amplitudes in the two groups. The high- and iow-tremor amplitudes as calculated by the DPD system are not neatly separated, although there is a significant difference in mean amplitude for the two groups. The other characteristics vary by differing amounts between the two groups. Centre frequency is distributed similarly for both groups. Harmonic index and tremor index show some separation, although the means are still within 1 SD of each other. Frequency dispersion separates the two groups slightly more. Therefore, the other three characteristics used in calculating the tremor index (centre frequency, frequency dispersion, and harmonic index), although somewhat correlated with amplitude, extract different information from the tremor. The differences in amplitude results from the DPD and LB systems, indicated by the large overlap in DPD amplitude be-

TABLE

1

DPD SYSTEM

Characteristic Amplitude Log(amplitude)* Centre freq. Freq. dispersion Harmonic index Tremor index

High-Amplitude Group (n = 12) 0.314 - 1.614 6.267 1.592 0.937 59.83

2 ? -c 5 k i

0.372 0.944 1.059 1.335 0.045 39.20

Low-Amplitude Group (n = 96) 0.095 -2.402 6.408 2.848 0.903 86.74

+ -t 2 ? z 5

0.036 0.291 1.083 1.048 0.050 27.80

Values are means t SDS of spectral characteristics, 54 subjects, both hands (high- vs. low-amplitude groups). *Amplitude is given because it is reported by the DPD system, but the distribution of log(amplitude) for our sample is closer to being Gaussian.

tween the high- and low-amplitude groups, suggested that further tests be done to check validity and consistency of the measuring systems. Validity Validity of the DPD system measurements was assessed by testing a small group of subjects simultaneously with the DPD and LB systems. Six subjects were tested four times each (two left, two right). The DPD stylus was held in the usual position and a light (
POSTURAL

TREMOR

MEASURING

99

SYSTEM

‘High’ tremor group

-3

-1

-2

0

1

0

1

Log intensity(m&Z)

‘Low’ tremor group

-3

-1

-2 Log

intensity (m&Z)

FIG. 3. Histograms of DPD tremor amplitude, for the high-tremor amplitude group (below).

tremor index were calculated from the acceleration spectra derived from the LB system and compared with the corresponding values from the DPD system (see Table 2). It should be noted that the correlation between the DPD and LB amplitudes is not as high if detrended displacement amplitude instead of acceleration is used with the LB system (for amplitude: 0.841; for log amplitude: 0.844). In fact, detrended displacement amplitude and acceleration amplitude, both calculated from the same LB data, had similar correlations (for amplitude: 0.851: for log amplitude: 0.859). If the displacement is not detrended, the correlation disappears entirely. The correlation coefficient for DPD acceleration amplitude vs. LB displacement amplitude (not detrended) was -0.096: for log amplitude. it was -0.154. We also calculated correlation coefficients between the DPD system amplitude (acceleration) and the LB system amplitude (detrended displacement) from the original sample of 54 subjects (see Table 3). Clearly, the simultaneous recordings by the two systems. when processed in the same way, produce essentially the same results, whereas our original recordings with the two systems, which were not simultaneous and differed also in the variable recorded (displacement vs. acceleration). produce very different results, even for something as basic as amplitude. Consistency To get an idea of how much variability there is over short time periods for the same subject (same hand). we conducted

amplitude group (above) and the low-tremor

another test with two trials for each hand, trials separated by 1-2 min (and exceptionally, up to 11 min). A different group of 20 subjects, referred by a local physiatry department, was tested with the DPD system. Correlation coefficients were calculated for each of the five characteristics. As a comparison, we calculated correlation coefficients (for detrended displacement tremor amplitude only) between two trials of the LB system (about 34 s apart) on the original sample of 54 subjects. Correlations for these have been calculated separately for the control group and the group of patients with Parkinson’s disease (see Table 4). Amplitude as measured by the DPD system is consistent between successive trials with a short delay between trials.

TABLE

2

CORRELATIONS BETWEEN SYSTEMS (DPD AND LB) FOR TREMOR AMPLITUDE AND SPECTRAL CHARACTERISTICS IN SIMULTANEOUS RECORDlNGS Characteristic

Trials

DPD DPD DPD DPD

vs. LB vs. LB vs. LB vs. LB

DPD vs. LB I? = 24 = 6 subjects

rho

ccntre freq.

0.055

freq. dispersion harmonic index amplitude log(amplitude)

0.8 19 0.896 0.989 0.989

X 2 hands

X 2 trials.

100

EDWARDS TABLE

3

TABLE

(‘ORREI,ATfONS BETWEEN TREMOR AMPLI’I [IDES AS CALCULATED BY DPD (ACCELERATION) AND LB (DETRENDED DISPLACEMENT) SYSTEMS

5

rho

(‘ontrol Group (!I = i’)

Chal-actcristics

II = IOX = 54 suhiects

amplitude log(amplitude) amplitude log(amplitudc)

0.2YS 0.444 0.270 0.475

X 2 hands.

Amplitude Lo&litude) C‘entre freq. Fry. dispersion Harmonic index Tremor index

0.2 12 - I.933 6.310 I.805 O.Y40 72.00 ,I

Frequency dispersion is quite consistent (i.e., a concentration of power in a small frequency range tends to remain) but other characteristics are less robust and tend to vary to a greater degree. even when the amplitude does not. The amplitude is similarly consistent across trials with the LB system for both patient and control groups (despite the presence of a tracking task between the two trials: see the Method section).

Amplitude (LB) Log(amplitude)(LB) *Both trials were included

I,

Characlrli\l~c

rho

40 40 40 40 40 40

centre freq. freq. dispersion harmonic index tremor index amplitude log(amplitudc)

0.736 0.812 0.263 0.575 0.945 0.946

LB vs. LB (control) LB vs. LB (control) LB vs. LB (patients)

66 66 42

LB vs. LB (patients)

42

amplitude log(amplitude) amplitude log(amplitude)

0.828 0.801 0.971 O.YO7

DPD DPD DPD DPD DPD DPD

vs. vs. vs. vs. vs. vs.

DPD DPD DPD DPD DPD DPD

42

0.1 13 i 0.136 -2.55Y z 0.798

0.093 2 2.405 2 6.475 i 3.1 IY L O.XYS ‘, ‘J2.03 t II

-

0.022

0.247 0.074 0.912 0.054 24.49

6-l

O.OhO i 0.034 -2.946 + 0.S 17

for the LB bystem.

Groups

It is expected that centre frequency, frequency dispersion, and harmonic index do not neatly separate the high- and lowtremor amplitude groups. In fact, if other measures were to be used that correlate highly with amplitude they would not carry any extra information. The fact that there was some separation with frequency dispersion and with harmonic index is probably due to the fact that higher amplitude tremors generally tend to be more concentrated in narrow fr-equency ranges. More surprising was that there was also considerable ovcrlap between the high- and low-tr-emor amplitude groups for the DPD tremor amplitude measure. although there was a significant difference in means for the two groups. A careful look at individual amplitude results revealed that a few subjects showed a high amplitude from the DPD system and virtually no tremor for the LB system and vice versa. Potential causes for these discrepancies are: I. imprecision in the DPD system (validity); 2. an inherent tendency of tremor amplitude to vary overtime with changing conditions (consistency); and 3. a difference between amplitude measures (acceleration vs. detrended displacement). Validity

4

CORRELATIONS BETWEEN FIRST AND SECOND TRIALS FOR TREMOR AMPLITUDE AND SPECTRAL CHARACTERISTICS (BOTH HANDS)

TI-ialc

:.

2 0.2Y2 c 0.73s z 0.82h 2 1.174 -c 0.033 z 39.00

DISCUSSION

High- vs. Low+Amplitude

Of the 54 subjects in the primary study, the one who had a large essential tremor was removed from the sample for this part of the study. to avoid skewing the results for the group without Parkinson’s disease. The values of the DPD system’s five characteristics were compared between the group with and without Parkinson’s disease, using the most affected hand of each subject (defined as highest DPD amplitude, or if amplitude was equal between the two hands, lowest tremor index) (set Table 5 and Fig. 4). The displacement amplitude as measured by the LB system is included in the table for comparison (worst hand defined as highest detrended displacement amplitude). There are differences in the distributions of the characteristics for the Parkinson’s and non-Parkinson’s groups but there is considerable overlap in every case. A one-sided t-test to determine whether the tremor index for the group with Parkinson’s disease is lower than for the group without Parkinson’s disease (null hypothesis: TI(P) 2 TI(NP); alternative hypothesis: TI(P) < TI(NP)) rejects the null hypothesis at the 95% level (p = 0.029).

TABLE

BEIJTER

SPECTRAL C‘HARAC‘TERISTICS OF THE C’ONTROL GROUf AND THft PATIENTS WITH PARKINSON‘S DISEASE (DPD ABOVE AND LB BELOW)

‘Trial5 LB 1 vs. DPD LB I vs. DPD LB 2 vs. DPD LB 2 vs. DPD

AND

The first of these potential causes of discrepancy is a yuestion of validity. The simultaneous recordings with the DPD and LB systems showed that this is not a primary factor. The spectra obtained in parallel fashion by the two systems were not identical, but the small discrepancies could be due to minor differences in processing (see Appendix). The correlation coefficients between parallel smoothed spectra are high enough to show that they are recording essentially the same data, and when the power in the spectrum is lumped into a single amplitude figure, the correlation is even more convincing. The centre frequency, as calculated from the two parallel recordings, was also very consistent, and the frequency dispersion and harmonic index only slightly less so. The lower correlation for frequency dispersion (0.819) seems largely to be due to the exceptional case with the spurious peak in the DPD spectrum: when it is removed. the coefficient becomes 0.937.

POSTURAL

TREMOR

MEASURING

101

SYSTEM b

a

-3

-2

-1

0

Log intensity

1

-3

-2

-1

5

1

(mls”2)

d

c

4

0

Log intensity

(mM2)

6

7

8

Centre frequency

9

4

5

6

7

Centre frequency

(Hz)

8

9

4

5

(Hz)

e

0

1

2 Frequency

3

4

dispersion

5

0

1

2 Frequency

(Hz)

3 dispersion

(Hz)

h

0.75

0.80

0.85

Harmonic

0

0.90

50

too Tremor

1 .oo

0.70

0.75

0.80

0.95

Harmonic

index

150

index

0

0.90

50

100 Tremor

0.95

1 .oo

index

150

index

FIG. 4. Histograms of each of the five DPD characteristics using the worst hand only. for the group with Parkinson’s disease (left) and the control group (right) for log amplitude (a. b). centre frequency (c, d), frequency dispersion (e. f), harmonic index (g. h). and tremor index (i. j).

The harmonic index, however, has a coefficient of about 0.89 (even with the exceptional case removed) and so appears to be slightly less robust with respect to minor differences in acquisition or processing methods. The problem of spurious low-frequency peaks in the DPD spectrum can best be dealt with by ensuring that the subject doesn’t rotate the pen at all during acquisition, by explanation, and, if necessary, redoing the test, because the frequency information is available instantaneously. This is an inherent concern with accelerometric systems.

The second potential cause of the discrepancies is a question of consistency. Our test-retest reliability study shows that amplitude is consistent between trials conducted within a few

minutes of each other (even more consistent than with the LB displacement amplitude, though there we had a tracking task between trials, which may have affected the tremor). Frequency dispersion was also quite consistent across trials, as was centre frequency, though with a slightly lower correlation coefficient. Harmonic index. however. was quite inconsistent across trials. Although this reassures us that the test is reliable as a system for measuring tremor amplitude, it does not preclude the likelihood that over longer periods of time tremor characteristics, amphtude in particular, can vary a great deal. In fact, there are considerable discrepancies between severity of postural tremor as determined by the DPD system and the LB system and as assessed by the neurologist on the same day, which can only be due to tremor coming and going between the tests. For example, the neurologist found no postural

102

EDWARDS

tremor for three of the subjects with Parkinson’s disease who had relatively high tremor amplitude measures from both the DPD system (worst hand amplitudes: 1.38, 0.15, 0.17 m/s*) and the LB system (worst hand amplitudes: 0.23, 0.30, 0.92 mm) including the highest for each system. Recall that for detrended displacement, high amplitude was defined as more than 0.17 mm and the normal range for the DPD system is 0.11 ? 0.03. Another three with low-tremor amplitudes according to both the DPD (worst hand amplitudes: 0.11,0.09.0.08 m/s*) and LB (worst hand amplitudes: 0.07, 0.07, 0.04 mm) results were assessed by the neurologist as having significant postural tremor. In another case, the DPD test found a large tremor in the right hand (0.23 m/s*), agreeing with the neurologist, but the LB system did not (0.05 mm). In yet another case, the LB system found a large tremor in the right hand (0.20 mm) reported by the neurologist, but the DPD system did not (0.10 m/s*). These differences cannot be due to inherent unreliability in the DPD measurements (or in the LB measurements) as the test-retest results as summarized in Table 4 are too consistent. Hence, they must be due to genuine changes in the amplitude of tremor of some subjects over the testing period (the neurological assessment, the DPD test, and the LB test in some cases spanned a period of 2 h or more). In fact, we have some LB recordings of tremor that visibly changed in amplitude over times of 30 s to several minutes (6). Displacement

vs. Acceleratiort

The third potential cause of discrepancies in amplitude measurements is the choice of whether to measure displacement or acceleration (or even velocity) amplitude. There is, of course, a clearly defined relationship between acceleration and displacement, and it is theoretically a simple matter to calculate one from the other in either the time or frequency domains (3,7,19). The basic effect is that acceleration (in relation to displacement) emphasises higher frequencies and suppresses lower frequencies. A pronounced tremor concentrated in a narrow frequency band will yield a high-amplitude measure in either case (unless the frequency is very low), but with a broad, noisy spectrum the effect will depend on how the power is distributed. It is certainly true that two oscillations of the same displacement amplitude, located at different frequencies. will yield different acceleration amplitudes and vice versa. The detrending removes the large-scale and very low-frequency component of the displacement data, which is not a part of tremor and is naturally supressed in acceleration measurement. However, the above effect is still present in the remaining data. In recordings of human tremor, this effect may be quite significant, in light of the comparisons made above, especially between our original LB and DPD results in Table 3, but even acceleration and displacement amplitude calculated from the same time series are not identical. Presumably, the neurologist, who assesses severity of tremor visually, is measuring displacement rather than acceleration amplitude. There has been considerable debate over which is preferable, and we do not resolve this debate here, but our results point out that there can be a significant difference between the two methods and that it is important to address this issue. Control Group vs. Group with Parkinson’s

Disease

Finally, the DPD system is designed to detect anomalies in tremor (compared to control subjects), so we asked if it could separate the groups with and without Parkinson’s disease. The

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distributions of most of the characteristics for the two groups were clearly different, but there were nevertheless considerable overlaps for all the characteristics. There were a few subjects with Parkinson’s disease with high tremor amplitude having a sharp narrow peak in the spectrum, which made the means for amplitude, harmonic index, and frequency dispersion different from those of the control group. However. many of the subjects with Parkinson’s disease had tremor that was well within the normal ranges in amplitude and in the other characteristics. Interestingly, the centre frequency was virtually the same in the two groups. The tremor index, which combines the four characteristics in a single number, showed the same overlap between the groups. Diagnosis on the basis of tremor index by itself, or any of the individual characteristics, would therefore not be very reliable. There are several possible factors contributing to these overlaps between results for Parkinson’s and non-Parkinson’s groups. First. the neurological assessment is itself uncertain: thcrc is a considerable error rate in diagnosis (15.17). Second, most of the subjects were in early stages of the disease (stages I and II), which increases the difficulty of detection (though this was the intention of the study). Some subjects may have been in a state of transition from normal to pathologic tremor. Third. most of the patients with Parkinson’s disease were on medication and had taken their medication on the day they were tested (the length of time before being tested varied). Medication generally reduces tremor to some degree, though not completely. Fourth, there is variation over time in amplitude of tremor. as mentioned above. so it is possible that some of the subjects with Parkinson’s disease did not have significant tremor at the moment of testing. In fact, during the experiment we noted that some patients with Parkinson’s disease did not have visible postural tremor whereas some control subjects had mild essential tremor. How well did the centre frequency, frequency dispersion, and harmonic index reported by the DPD system perform. in general? In our study, ccntre frequency did not vary much in distribution between the group with and without Parkinson‘s disease, or between the “high-amplitude” and “low-amplitude” groups. Most of the literature, however, suggests that subjects with Parkinson’s disease should have lower frequency tremor. This is perhaps a matter of how one defines “frequency of tremor.” In the case of a pronounced, single peak in the power spectrum, there is no ambiguity, but in a broad, noisy spectrum there are many ways to select a frequency to try to reflect the tremor by a single figure. Taking the largest peak is one way, but is subject to random fluctuations in the peaks and may even depend significantly on the frequency resolution in the spectrum, though smoothing or other means of spectral estimation reduce the variance of the power estimates. Centre (median) frequency is an attempt to give a stable measure that is always well defined. For pronounced tremors, it will correspond with the dominant peak exactly, but in other cases there may be problems. If the spectrum has two peaks of similar size. for example, the centre frequency may fall between them in a region with little power. In this case, a small change in power in the peaks could cause a large change in the centre frequency. However, in both the simultaneous recordings by the DPD and LB systems and in the test-retest recordings with the DPD system, centre frequency was reasonably consistent. Frequency dispersion showed some separation between high-amplitude and low-amplitude groups as we11 as between the group with and without Parkinson’s disease. but in both

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with considerable overlap. It was fairly consistent in the test-retest results with the DPD system and in the simultaneous recordings, though less consistent than centre frequency or amplitude. Again, if the boundaries of the region of the spectrum around the centre frequency having 68% of the power fall in an area of low power, small changes in distribution could cause large movements in these boundaries. Harmonic index also separated the high-amplitude and low-amplitude groups and the group with and without Parkinson’s disease to some extent. but was very unreliable in the test-retest experiment and slightly less even in the simultaneous recording experiment. This measure is perhaps unstable because it depends on the normalization of the power spectrum to the height of the highest peak. Random differences from trial to trial. or differences in processing methods. can cause significant changes in the height of a peak. which will have a correspondingly large effect on the harmonic index. If a peak becomes half the height but twice as wide, containing the same amount of power, for example, the area under the spectrum will more than double, and so the harmonic index will be twice as far from 1.0. There is clearly some value in a measure like this, but it would be better if defined so as to be more stable across trials. If there is something anomalous about the tremor of the subjects with Parkinson’s disease aside from amplitude, it is not clearly evident in the spectral characteristics reported by DPD. The DPD system does give a graphical display of the power spectrum (and the spectrum can be exported to an ASCII file) so there is the possibility of looking more closely at details of the spectrum or of calculating other characterirtics from it. cases,

Concluding

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Remarks

We have verified that the DPD system accurately measures tremor spectra and certain characteristics of tremor. Some aspects of the data acquisition process used are not entirely clear from the documentation provided. although most of these points we were able to clear up later by contacting the company. The DPD system is easy to use, robust. and portable. though care must be taken to make sure the test is done correctly (e.g., no rotation of pen), and this should also be considered in comparing it with other systems. What is evident from our study, however, is that accuracy is not the only concern. Other issues that must be addressed include: what are the best characteristics (in terms of specificity and reliabilitv) of tremor to measure? and how are changes in tremor over time to be dealt with? Even tremor amplitude proved not to be a clear-cut issue. Tremor amplitude calculated from the displacement data of the LB system is not highly correlated with the amplitude recorded by the DPD system (Table 3). This seems to be due partly to changes in the tremor over time and partly to the difference between acceleration and displacement data. A high amplitude in displacement (even when detrended according to the scheme described above) does not always imply a high amplitude in acceleration or vice versa, so these should be considered different characteristics. Acceleration amplitude did not clearly separate all patients with Parkinson’s from the control subjects either, although the ones with the largest tremors stood out. Centre frequency in acceleration spectra did not seem to be very specific. at least to patients with Parkinson’s disease. Frequency dispersion appeared to be somewhat useful in separating the patients with Parkinson’s disease from the control subjects, and was fairly reliable across trials.

Harmonic index as defined by DPD was also useful in separating the groups but was not a very stable measure. Thus, whereas it is clear that the characteristics reported by DPD have a general bearing on distinguishing pathologic tremor, they are crude tools. The DPD system did clearly identify subjects with very pronounced tremors, though many of the patients with Parkinson’s disease were not thus identified. The one subject with a moderate essential tremor also showed clearly abnormal results. It does not appear to be sensitive enough to identify subclinical cases or to differentiate between different types of tremor (such as essential and parkinsonian tremor). It should be noted that we used the testing procedures suggested by the DPD company. In the light of our results and comments below. it might be possible to improve the performance of the system by having the subject perform a mental task such as counting backwards during testing. In addition, most patients tested were on medication. Although this means that we cannot draw conclusions about similar patients without medication, the system is really most useful if it can detect the pathology even when it is not visibly evident. If we are to do better in understanding and diagnosing different types of tremor, we will need measures that are, if possible, more specific to pathology or to particular pathologies. but are still stable and reliable. If amplitude is to be used, the question of whether to use displacement or acceleration (or velocity) or a combination must at least be addressed. Aside from spectral characteristics, it may be that significant information is held in the morphology of tremor. This has apparently not been studied. The question of fluctuations in aspects of tremor over time seems particularly important. In principle. there seem to be three possibilities for dealing with this issue. One way is to find characteristics of tremor, if they exist, which are insensitive to transients but sensitive to real underlying neurological differences. so that, for example, changes in anxiety or fatigue levels of a subject would not significantly affect results (6). Another way (as mentioned above) is to find experimental methods to ensure that an intermittent tremor is active during recording (without seriously altering the tremor due to fatigue). Or, finally, the fluctuations in tremor could themselves be studied. After all, transitions in tremor may hold significant information themselves (19). ACKNOWLEDGEMENTS

The authors wish to acknowledge financial support from the Cree Board of Health and Social Services of James Bay, the Natural Sciences and Engineering Research Council of Canada, and the Fonds pour la Formation de Chercheurs et I-Aide a la Recherche (Quebec). We would also like to thank Dr. John Heeboll of Danish Product Development, Ltd. for his patient and enthusiastic assistance with the many questions we had regarding the DPD system. APPENDIX:

C’ALCULATING ACCELERATION FROM DISPLACEMENT DATA

AMPLITUDE

An acceleration spectrum corresponding to the one produced by the DPD system can be calculated from displacement time data by differentiating the displacement time series twice, applying the same filter as is used by the DPD system and then extracting the spectrum. It can also be done by applying the filter to the displacement data, extracting the displacement spectrum from this and then multiplying the spectrum by the appropriate function to get the acceleration spectrum (3,19). The latter method may be better in that it avoids the problem of noise amplification in the differentia-

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tion process. Both methods were tried and the second method gave slightly higher correlations to the DPD results. Here are the details of the procedure. The DPD system starts its data recording 1.5 s after the keystroke that begins the test. In its analysis, it uses the following 5.192 s of data. Our LB recordings were started by pressing a key at the same time as the DPD starting keystroke, as nearly as possible. Then the appropriate 8.192 s of data were extracted for analysis. First, the I and y displacement signals were filtered using the same type of low-pass filter as used by DPD (5). except

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that because our data were collected at 200 Hz rather than 500 Hz, a 12-point filter rather than a 32-point filter was used, and then subsampling was done at 33.33 Hz (i.e.. every sixth point) rather than 31.25 Hz (i.e., every 16th point). Then the spectra for each series (X and y) were calculated and were converted to acceleration spectra by multiplying by (2rrf)4, where fis frequency in Hz. Finally, the two spectra were added (componentwise), which is equivalent to taking a Pythagorean sum of .r and y acceleration values because the power spectrum values have units of acceleration squared.

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