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Japanese Journal of Comprehensive Rehabilitation Science (2020)

Original Article

Assessment of finger movement characteristics in dementia patientsusing a magnetic sensing finger-tap device
Junpei Sugioka, OTR,1,2 Shota Suzumura, OTR, MSc,1 Yasuhiro Kawahara, PhD,2
Aiko Osawa, MD, PhD,1 Natsumi Maeda, OTR,1 Misato Ito, OTR,1 Taishi Nagahama, OTR,1
Katsumi Kuno, OTR,1 Kenta Shiramoto, OTR,1 Shiori Kizuka, OTR,1 Tomohiko Mizuguchi,3
Yuko Sano, PhD,4 Akihiko Kandori, PhD,5 Izumi Kondo, MD, PhD1
Department of Rehabilitation Medicine, National Center for Geriatrics and Gerontology, Aichi, Japan
Program of Human Life and Health Sciences, Graduate School of Arts and Sciences, The Open University ofJapan, Chiba, Japan
3
Optronics Division, Maxell, Kanagawa, Japan
4
Center for Technology Innovation - Healthcare, Hitachi, Research and Development Group, Tokyo, Japan
5
Center for Exploratory Research Center, Hitachi, Research and Development Group, Tokyo, Japan1

2

ABSTRACT
Sugioka J, Suzumura S, Kawahara Y, Osawa A, Maeda
N, Ito M, Nagahama T, Kuno K, Shiramoto K, Kizuka
S, Mizuguchi T, Sano Y, Kandori A, Kondo I.
Assessment of finger movement characteristics indementia patients using a magnetic sensing finger-tap
device. Jpn J Compr Rehabil Sci 2020; 11: 91‐97.
Objective: Differences in finger movement characteristics
during finger-tapping movements among Alzheimer’s
Disease (AD) patients, Mild Cognitive Impairment(MCI) patients, and healthy elderly individuals were
examined using a magnetic sensing finger-tap device(UB-2; Maxell, Tokyo), and relationships withcognitive function were investigated.
Methods: Finger-tapping movements were measured
and multiple comparisons using mean values ofparameters from each group were conducted.
Cognitive function was evaluated using the MiniMental State Examination (MMSE), and Spearman
rank-correlation coefficients were used to analyze
relationships between these parameters and MMSE
Correspondence: Junpei Sugioka, OTR
Department of Rehabilitation Medicine, National Center
for Geriatrics and Gerontology, 7‐430 Morioka-cho, Obu,
Aichi 474‐8511, Japan,
E-mail: sugioka@ncgg.go.jp
Accepted: April 26, 2020.
Conflict of interests: Yuko Sano and Akihiko Kandori areemployees of Hitachi, Ltd., and Tomohiko Mizuguchi is an
employee of Maxell, Ltd. National Center for Geriatrics
and Gerontology conducts joint research with Hitachi, Ltd.,and Maxell, Ltd. The equipment used in this study was lentby Maxell, Ltd., to the National Center for Geriatrics andGerontology.
©Kaifukuki Rehabilitation Ward Association 2020
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scores.
Results: Significant differences were observed in total
traveling distance, standard deviation (SD) of contact
duration, SD of inter-tapping interval, and SD of phasedifference between left- and right-hand tapping.
MMSE score showed a weak negative correlation with
the SD of contact duration of the left hand (r = -0.28,
p < 0.05). Weak positive correlations were observed in
total traveling distance of the left hand (r = 0.3, p <0.05) and right hand (r = 0.25, p < 0.05) and the inphase task for the right hand (r = 0.28, p < 0.05).
Conclusion: These parameters may represent finger
movements that are characteristic of AD and MCI.
Key words: Alzheimer’s Disease (AD), Mild Cognitive
Impairment (MCI), finger movement characteristics,
finger-tapping
Introduction
About 6.3 million individuals in Japan suffer fromdementia, due to the aging population and subsequent
increase in prevalence of morbidity due to aging, andthis figure is expected to reach 7 million by 2025 [1].
The number of dementia patients is expected tocontinue increasing dramatically, and urgent measures
are thus needed.
Dementia can be classified into three major
categories: Alzheimer’s Disease (AD); cerebrovasculardementia; and Lewy body dementia. AD accounts for
50‐70% of all dementia cases and is a diseaseassociated with loss of memory and progressive
declines in cognitive function [2]. Due to theimportance of early diagnosis, many clinical studies
have targeted individuals with Mild Cognitive
Impairment (MCI), a borderline state between normal
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Sugioka J et al.: Assessment of finger movement characteristics in dementia patients through finger-tapping movements

aging and dementia proposed by Petersen et al. [3].
Recent research has shown that patients with dementia,
including MCI, in the early stages exhibit gait
disorders. Early motor impairments may thus assist in
the detection of dementia [4].
We have focused on finger movements (fingertapping movements) as a simple method to evaluate
motor impairment in dementia patients. We used a
device for measuring motor function of the fingers(UB-1 magnetic sensing finger-tap device; Hitachi
Computer Peripherals, Kanagawa) in a preliminary
study of finger-tapping movement in dementia
patients, and identified parameters that captured thecharacteristic finger movements of dementia patients[5]. First, in that preliminary study, differences inparameters were compared between an AD/MCI group
and a healthy elderly group. Significant differenceswere observed in three parameters: total traveling
distance; standard deviation (SD) of contact duration;and SD of inter-tapping interval. Second, analysis of
the associations between these parameters and severityof dementia using the Mini-Mental State Examination(MMSE) revealed a positive correlation with total
traveling distance and negative correlations withenergy balance, SD of contact duration, SD of intertapping interval, and SD of phase difference between
left- and right-hand tapping [5].
The first objective of the present study was to use
UB-2 (Figure 1), as an improved version of the abovementioned tapping device, to verify the samecharacteristic finger movements as UB-1 and confirm
the associations with MMSE. Second, as AD and MCI
were analyzed as one group for comparisons in the
preliminary study, AD and MCI were split and three-group comparisons were performed to determine
whether changes in characteristic finger movements
can be detected from the MCI stage, since early
detection is crucial for MCI.
Subjects
1. Patient backgroundThe subjects were first-time patients in the Centerfor Comprehensive Care and Research on Memory
Disorders at the authors’ hospital, who had been
diagnosed with either AD or MCI. The breakdown of
the subjects was as follows: AD group, 44 patientswith AD (mean age, 74±7 years); MCI group, 20
patients with MCI (mean age, 77±4 years); and Control
group, 57 healthy elderly individuals (mean age, 74±7
years). The Control group comprised family members
who accompanied the AD and MCI patients to thehospital. Controls led socially independent lives, had
no history of attending a memory disorder outpatient
clinic and had no problems with cognitive function.
MMSE score [6] ≥ 28 was the condition for analysis.
All subjects were right-handed. Exclusion criteria
were as follows: presence of higher brain dysfunction
such as impaired consciousness, aphasia, or apraxia;
or marked paralysis or finger dexterity impairment due
to conditions such as stroke.
2. Ethical considerations
All subjects or their family members were given
detailed verbal and written descriptions of the present
experiment and consent was obtained from eachsubject prior to enrolment. Approval for the present
study was obtained from the Ethics and Conflict ofInterest Committee of the National Center for
Geriatrics and Gerontology (Approval No. 623-7).
Methods
1. History-taking and assessment
The subjects were asked to complete a medical
questionnaire to collect background information. The
MMSE was administered to quantify the severity ofcognitive function.

Figure 1. Magnetic sensing finger-tap device (UB-2)
Yellow cables are attached to the thumb and index
finger of the left hand, and red cables are attached tothe thumb and index finger of the right hand. The
device itself is connected to a computer. Wave profiles
during finger-tapping can be monitored on thecomputer. The UB-2 is lighter and more portable thanthe UB-1.

2. Instrumentation techniques and measuring
devices
The UB-2 magnetic sensing finger-tap device(Maxell, Tokyo) was used (Figure 1) as the measuring
device. This device is a more portable version of theUB-1. With magnetic sensors attached to the thumband index finger, finger-tapping movements(repeatedly bringing the tips of the two fingers together
and apart) were performed. Finger-tapping movements
comprised unimanual tapping movements (dominant
hand task and non-dominant hand task), an in-phasetask (simultaneous right and left tapping movements),
and an anti-phase task (alternating right and left

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Figure 2. Finger-tapping (bringing the tips of the thumb and index finger together and apart).
(1) Non-dominant hand movement: Finger-tapping as fast as possible with the left thumb and index finger. (2)Dominant hand movement: Finger-tapping as fast as possible with the right thumb and index finger. (3) In-phase
movement: Simultaneous finger-tapping as fast as possible with both hands. (4) Anti-phase movement: Alternating
finger-tapping between the right and left hands as fast as possible. The distance between the two fingers is kept at
about 3‐4 cm apart when conducting Steps (1) to (4), and the task is performed for 15 s.
tapping movements) (Figure 2). Before measuring
each movement, we asked the subject to tap “as fast as
possible” for an approximately 5-s practice run to test
whether the subject understood the tapping movements.
After this practice, the subjects were asked to perform
each of the task movements in the following order:
non-dominant hand task, dominant hand task, in-phasetask, and anti-phase task. Measurements were takenfor 15 s. After measuring and recording the distance
between the fingers at 10-ms intervals of tapping
movements, the magnetic sensing finger-tap device
used in this study also calculated 44 parameters.
In the preliminary study, parameters such as total
traveling distance, SD of contact duration, SD of intertapping interval, energy balance, and SD of phasedifference between left- and right-hand tapping
appeared to represent useful characteristic fingertapping movements of dementia patients [5]. The
present study therefore also analyzed total traveling
distance, energy balance, SD of contact duration, SDof inter-tapping interval, and SD of phase difference
between left- and right-hand tapping. Total traveling
distance was the sum of the distance traveled during
movement of the two fingers, regardless of whether
the fingertips came into contact. This value represents
the total amount of exercise. Energy balance is theratio of the integrated sum of squares of positive
speeds to the integrated sum of squares of negative
speeds, representing the balance of speeds between
finger movements apart and back together. SD ofcontact duration is the dispersion of time while thefingers are together. SD of inter-tapping interval is the

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dispersion of inter-tapping interval (time difference
between the minimum points of two adjacent taps).
When one inter-tapping interval is considered as 360°,
the SD of the phase difference between left- and righthand tapping was taken as the dispersion of angular
representation showing the time lag between left andright hands. The SD of phase difference between theleft- and right-hand tapping is a parameter calculated
only for the in-phase and anti-phase tasks.
3. Data analysis
The following parameters were extracted frommeasured data as finger movement characteristics:
total traveling distance, energy balance, SD of contact
duration, SD of inter-tapping interval, and SD of phasedifference between left- and right-hand tapping. The
Tukey-Kramer test was used to conduct multiple
comparisons of differences between mean parametervalues of the three groups (AD, MCI, and Control
groups). The Spearman rank correlation was used todetermine associations between finger movement
characteristics and cognitive function (MMSE). The
level of statistical significance was set at p < 0.05 andSPSS Statistics version 25.0 statistical analysis
software (IBM Japan, Tokyo) was used.
Results
1. Comparison of parameters among the threegroupsTable 1 compares the parameters among each group.
Except for the anti-phase task, total traveling distance
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Table 1. Comparison of parameters among the three groups.
Measured value ± SD
Parameters

Task

AD

MCI

p-Value
Control

Non-dominant hand 4.515±1.755
4.963±1.595
5.545±1.793
Dominant hand
4.799±1.878
5.347±2.061
6.157±1.515
In-phase
Total travelingLeft
4.684±1.888
4.851±1.673
4.851±1.673
Right
4.692±1.683
5.570±1.983
5.846±1.589
distance
Anti-phase
Left
4.221±1.723
4.119±1.297
4.981±1.620
Right
4.472±1.904
4.879±1.765
5.200±1.775
Non-dominant hand 0.803±0.149
0.808±0.122
0.848±0.129
Dominant hand
0.837±0.165
0.832±0.132
0.823±0.135
In-phase
Left
0.769±0.141
0.808±0.145
0.826±0.154
Energy balance
Right
0.801±0.178
0.828±0.105
0.819±0.140
Anti-phase
Left
0.638±0.157
0.679±0.193
0.672±0.160
Right
0.598±0.199
0.610±0.172
0.585±0.134
Non-dominant hand 0.034±0.023
0.030±0.012
0.023±0.009
Dominant hand
0.026±0.015
0.027±0.016
0.019±0.008
In-phase
SD of contact
Left0.029±0.015
0.030±0.011
0.021±0.008
Right
0.025±0.017
0.022±0.007
0.018±0.006
duration
Anti-phase
Left
0.058±0.033
0.062±0.036
0.047±0.043
Right
0.065±0.053
0.063±0.054
0.044±0.033
Non-dominant hand 0.082±0.206
0.046±0.018
0.033±0.015
Dominant hand
0.049±0.089
0.034±0.016
0.024±0.012
In-phase
SD of interLeft
0.044±0.037
0.042±0.028
0.029±0.012
Right
0.042±0.046
0.031±0.019
0.024±0.011
tapping interval
Anti-phase
Left
0.099±0.069
0.102±0.056
0.087±0.149
Right
0.090±0.058
0.103±0.090
0.066±0.046
SD of phase
In-phase
62.052±80.884 36.112±23.004 35.490±23.022
difference
between the left
hand and right Anti-phase73.957±39.360 87.929±112.469 60.704±30.718
hand tapping

AD vs. MCI vs.
control control
0.013
0.411
0.001
0.180
0.002
0.003

0.057
0.805

0.057
0.126
0.248
0.882

0.103
0.777
0.498
0.967

0.141
0.827

0.879
0.972

0.576
0.917
0.004
0.014

0.984
0.827
0.203
0.018

0.005
0.020

0.020
0.387

0.329
0.063
0.128
0.066

0.304
0.245
0.919
0.766

0.014
0.009

0.137
0.658

0.866
0.114

0.863
0.051

0.033

0.999

0.470

0.146

In comparisons between the AD and Control groups, total traveling distance except for the anti-phase task wassignificantly smaller and the SD of contact duration was significantly larger in the AD group.
In addition, the in-phase task differed significantly for SD of inter-tapping interval and SD of phase difference
between left- and right-hand tapping.
The MCI and Control groups showed significant differences in SD of contact duration between the dominant handtask and in-phase task for the left hand.
Values of p < 0.05 are shown in red.
was significantly smaller for the AD group than for theControl group, and the SD of contact duration was
significantly larger in the AD group than in the Control
group. A significant difference in SD was seen forinter-tapping interval during the in-phase task (rightand left), indicating rhythm irregularities. A significant
difference in the SD of phase difference was seen
between left- and right-hand tapping during the inphase task, indicating a large dispersion of time lag
between the two hands.
When the MCI and Control groups were compared,a significant difference was observed only in the SD ofcontact duration during the dominant hand task andthe in-phase task (left hand). Similarly, a significant
difference was seen when these comparisons weremade between the AD and Control groups. No
significant differences were apparent in any of theparameters for anti-phase tasks. No significant
differences were seen in any of the parameters whenthe AD and MCI groups were compared.
2. Relationship between finger-tapping movement
and MMSE
A weak negative correlation (r = -0.28, p < 0.05)
was observed in the non-dominant hand task of the SD
for contact duration. A weak positive correlation was

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Figure 3. Associations between parameters and MMSE score.
A weak negative correlation (r = ‐0.28, p < 0.05) is observed in the non-dominant
hand task for the SD of contact duration. A weak positive correlation is observed in
the left hand (r = 0.3, p < 0.05) and right hand (r = 0.25, p < 0.05) of total traveling
distance as well as in the right hand in the in-phase movement task (r = 0.28, p < 0.05).

observed for the left hand (r = 0.3, p < 0.05), righthand (r = 0.25, p < 0.05), and right hand of the inphase task (r = 0.28, p < 0.05) and total traveling
distance (Figure 3). No correlations with otherparameters were identified.
Discussion
Studies on finger functions in elderly individuals
have identified declines in finger dexterity and muscle
strength with aging [7, 8], and finger-tapping
movements show fewer taps and delayed tapping
response times [9]. Moreover, studies on finger
function in dementia patients have shown deteriorations
in fine motor control [10], and have also reported
longer intervals between finger-tapping and fewer taps
in AD and MCI patients compared to healthy elderly
individuals [11].
In line with the preliminary study, a comparison
between the AD and Control groups in the present
study showed significant differences in parameterssuch as total traveling distance, SD of contact duration,and SD of inter-tapping interval. Unlike the preliminary

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study, this investigation also showed a significant
difference in parameters such as the SD of phasedifference between left- and right-hand tapping. The
newly identified difference may have been due to thefact that AD and MCI were split, and comparisonswere made among the three groups. In AD patients,
delayed contact duration during finger-tapping,
reduced amount of exercise, irregular rhythm, andtime lag between the two hands may representcharacteristics of finger movements.
Subjects in a previous, tablet-based study were
given the task of touching markers that appeared on
the tablet screen following a certain rhythm, and theresults showed that the contact duration in the group ofpatients with AD and MCI was significantly longer
than that in healthy elderly individuals [12]. In thepresent study, a significant difference in the SD ofcontact duration of the dominant hand task and the inphase task was seen for the MCI group compared to
the Control group. A significant difference incomparisons between the AD and Control groups was
also apparent. The delay in contact duration during
finger-tapping is considered to be a clinical finger
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Sugioka J et al.: Assessment of finger movement characteristics in dementia patients through finger-tapping movements

movement characteristic, but might actually be acharacteristic pattern observed from the MCI stage, as
an earlier stage. In the present study, no significant
differences between the MCI and Control groups were
found with parameters other than the SD of contact
duration. This may be due to the large variability insample size between the MCI and Control groups.
Furthermore, in comparisons between the AD andControl groups, significant differences were only
absent for anti-phase tasks. Executing the anti-phasetask may have also been difficult for healthy elderly
individuals and fatigue may have had some effect, as it
was the last task in order of performance. No significant
differences were identified in any of the parameterswhen the AD and MCI groups were compared. Thismay have been affected by the severity of AD. Subjects
were first-time patients in the Center for Comprehensive
Care and Research on Memory Disorders at theauthors’ hospital and the AD group may have included
subjects that were relatively closer to the MCI level.
When the association between finger function andcognitive function was examined, a negative
correlation was found between the non-dominant handtask of the SD of contact duration and MMSE score.
As mentioned previously, delayed contact duration ishighly likely to represent an early stage characteristic
observed from the MCI stage. Furthermore, MMSE
score correlated positively with left hand, right hand,
and right hand in-phase tasks of the total traveling
distance. Total traveling distance as a parameter isaffected by speed and the number of taps. Previous
studies have reported a decline in finger-tapping speed[13] and a reduced number of finger taps [11] among
AD patients, and the present results were in line withthose of previous studies. Parameters related to the SDof contact duration and total traveling distance may
likely be factors contributing to finger functions when
the severity of cognitive function worsens.
While finger movements are intricately linked tovarious regions and locations in the brain, muchremains unknown. Bimanual coordination involves
the corpus callosum [14] and the basal ganglia [15],while rhythmic tapping involves the motor cortex,
supplementary motor area, basal ganglia, thalamus,
and cerebellum [16]. Corpus callosum atrophy andmicroscopic changes in the brain have been reported
as early changes in AD [17, 18]. Some form of minor
motor impairment is thus highly likely to be present
prior to the onset of dementia or perhaps during the
MCI stage, which is an early stage of dementia.
When Perri et al. [19] conducted a study targeting
MCI subjects, they reported a 21.4% annual conversion
rate to dementia. According to Davis et al. [20], theannual conversion rate to MCI due to AD was in therange of 4‐10%. Various studies have examined
conversion rates not limited to these, and while noconsensus has yet been reached, early detection of the
MCI condition is clinically significant.

In recent years, early detection of AD has been
conducted using cerebrospinal fluid biomarkers such as
Aβ, total tau, and phosphorylated tau [21, 22] and tests
such as magnetic resonance imaging [23], single photon
emission computed tomography [24], and positronemission tomography [25]. These measurements need
to be taken at a medical facility, placing limitations on
the measurement setting, imposing financial andphysical burdens on subjects, and requiring more time
for measurement and analysis. However, themeasurement device used in the present study imposes
little burden on the subjects, is unaffected by the setting,and is easy to use.
In the present study, differences among the AD,
MCI, and Control groups were examined using amagnetic sensing finger-tap device, with the analysis
focused on items such as total traveling distance,energy balance, SD of contact duration, SD of intertapping interval, and SD of phase difference between
left- and right-hand tapping. Significant differenceswere observed in the comparison of these parameters
between the AD and Control groups. A significant
difference was also found in the SD of contact duration
between the MCI and Control groups. This suggeststhat these parameters may be used as one method of
evaluation for capturing characteristic finger
movements in AD and MCI.
Various limitations of the present study also need tobe considered. First, the sample size for the MCI groupwas small and variability in sample sizes was evident
among groups. Second, while the severity of dementia
can be assessed using methods such as the Clinical
Dementia Rating [26], the present study did notconduct any investigations according to the degree ofseverity. Third, no detailed examinations according to
the type of MCI were performed. Fourth, declines inattention and performance functions have beenreported with dementia [27], but these were notinvestigated in the present study. Fifth, brain functions
during finger-tapping were not analyzed in detail.
Sixth, the effects of fatigue or muscular endurance oneach of the individual subjects were not considered.
When the MCI and Control groups were compared,
p-values of 0.1 were observed for the dominant handand left hand for the anti-phase task of total traveling
distance, and the left hand for the in-phase task andright hand for the anti-phase task of the SD of intertapping interval. When sample size analyses of theseparameters were conducted, we found that thefollowing sample sizes were required: 66 subjects
each for the dominant hand of the total traveling
distance; 43 subjects each for the left hand in the antiphase task of the total traveling distance; 45 subjects
each for the left hand in the in-phase task of the SD ofinter-tapping interval; and 60 subjects each for theright hand in the anti-phase task of the SD of intertapping interval.
In future studies, we intend to increase the number

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of subjects, identify parameters with high ability todetect identifying finger movement impairments indementia patients, and examine their use as early
diagnostic tools for dementia and MCI.
Acknowledgment
This work was supported by JSPS KAKENHI Grant
Number JP19K11339.

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