Annals of Case Reports

Kitai K, et al. Ann Case Rep: 9: 101950
www.doi.org/10.29011/2574-7754.101950
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Case Report

Verifying the Efficacy of a Tactile Perceptual
Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Reportand Literature Review
Ken Kitai1,2*, Daiki Ito2, Shin Murata2, Osamu Katayama2,3, Takayuki
Kodama2
Rehabilitation Department, Maizuru Red Cross Hospital, Maizuru City, Kyoto Prefecture, Japan1

Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto City, Kyoto Prefecture, Japan2

Department of Preventive Gerontology, National Center for Geriatrics and Gerontology and Social Science Research Center, Obu City,
Aichi Prefecture, Japan

3*Corresponding author: Ken Kitai, Rehabilitation Department, Maizuru Red Cross Hospital, 624-0906, 427 Kuratani, Maizuru
City, Kyoto Prefecture, Japan
Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination
Stimulation Approach for Individuals with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report.
9: 1950. DOI:10.29011/2574-7754.101950
Received: 24 August 2024, Accepted: 28 August 2024, Published: 30 August 2024
Abstract
Purpose: To investigate the effects of tactile discrimination feedback sensory compensatory system device training on finger
sensory-based motor dysfunction after cervical cord injury.
Case Presentation: A patient with finger sensorimotor dysfunction following cervical cord injury underwent treatment using
an ABB design, with each treatment period lasting 1 week. The patient performed daily pegboard, building block stacking, andmaterial identification task tests over a 1-week period. The Purdue Pegboard Test, a behavioural measure, and the Numbness
Numerical Rating Scale, a sensory function assessment tool, were administered daily. From these tests, the Tau-U, a statisticalmeasure of the intervention effect size, was calculated. Additionally, as a physiological measure, an electroencephalogram wasrecorded daily for 1 min during the pegboard task. The coherence values of the electroencephalography frequency bands of thetheta (4–8 Hz) and mu (8–12 Hz) waves of Pz–Fz, a sensorimotor information processing index, were calculated, and the meanvalue of each phase was calculated for comparison and validation.
Result: After the device intervention, the theta and mu waves in the sensorimotor domain were attenuated. Motor function andnumbness of the right finger improved.
Conclusion: Training with a tactile discrimination feedback sensory compensatory system device may improve finger sensorimotor
function and contribute to shortening treatment duration.

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Ann Case Rep, an open access journal
ISSN: 2574-7754

Volume 09; Issue 04

Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report. 9: 1950. DOI:10.29011/2574-7754.101950

Keywords: Finger Sensorimotor Dysfunction; Tactile
Discrimination Feedback; Sensory Compensatory System Device;
EEG Frequency Analysis; Motor Learning.
Introduction
Injuries to the cervical spinal cord tend to cause motor dysfunctionof the finger due to damage to the conduction pathways in thefinger-controlled areas [1,2]. The hand and finger functions
enable essential human processes, including eating and excretion,
to survive in daily life. Therefore, improving upper limb motor
function, including that of the fingers, is of the highest priority
among physical functions in individuals with cervical spinal
cord injuries [3]. According to Peckham et al. [4], finger function
improves after cervical spinal cord injury, and the ability to perform
activities of daily living contributes to a significant improvement
in quality of life. Therefore, rehabilitation aimed at improving thefinger motor function after cervical spinal cord injury is important.
Sensory dysfunction of the finger inhibits upper limb motor
function from improving following cervical cord injury. Cervical
cord injury causes numbness in the fingers in 82% of cases due
to damage to sensory afferent pathways, and patients with suchinjuries are more likely to have finger sensory dysfunction [5,6].
To manipulate an object, fingers rely on sensory informationfrom the finger pads to generate the muscle activity necessary to
perform the action [7]. When finger sensory dysfunction occurs,
obtaining friction information from the finger pads becomes
impossible, making object manipulation difficult. This condition
is known as finger sensorimotor dysfunction and greatly impairs apatient’s ability to perform activities of daily living [8]. Therefore,
improving sensorimotor function after cervical spinal cord injury(SCI) is essential.
Task-oriented approaches have been used to restore impaired
motor functions. With this approach, patients actively performthe desired movements under the desired motor task conditions[9]. A task-oriented approach improves the motor function moreeasily as time progresses and the extent of rehabilitation increases[10]. Yang et al. [11] showed that the motor function of theupper limbs, including the fingers, can be improved by training
for at least 6 h a week. Therefore, the quantitative aspects of thisapproach are important for motor function recovery. However,Taub et al. [12] reported that even if a person is able to actively
and repeatedly perform a desired movement, their ability to learn
the movement declines if the desired movement continues tofail owing to finger sensorimotor dysfunction. In addition, metaanalyses on task-oriented and high frequency approaches haveoften excluded patients who present with abnormal perceptions of
the upper extremity or hand [13]. Thus, to regain motor functionin cervical spinal cord injury, in addition to quantitative aspects
such as the number of approaches and approach time, patients withsensorimotor dysfunction of the fingers must be made aware of2
Ann Case Rep, an open access journal
ISSN: 2574-7754

how to perform movements correctly. Therefore, the qualitative
aspects of this approach are important.
Hubbard et al. [14] reported that sensory feedback informationaccompanying movements improves the quality of the approach.
This may be because the brain can synchronously process the
motor intention and sensory feedback of the treated limb. Whenthe motor intention and sensory feedback appropriate for thedesired movement are processed synchronously (within 250 ms)
in the brain, a sense of agency is created, whereby the person
feels that they are performing the movement [15]. This sense ofagency increases activity in the premotor cortex and corticospinal
tract, thereby improving upper-limb performance [16]. Thesefindings suggest that real-time feedback of the sensory informationaccompanying movements may improve the quality of theapproach. Visual stimulation is generated as fingers move [17-19],
electrical stimulation [20,21] and auditory stimulation [22]Realtime feedback approaches using compensatory sensory modalities
have also been employed. Studies using these approaches havereported that real-time feedback stimulation that matches handand finger movements enhances the sensorimotor areas in thebrain that are important for motor learning, and improves handand finger voluntariness [19-22].
The manipulation of an object is made possible by the continuous
input of friction information generated between the finger abdomen
and the object as sensory information, as well as by the generationof hand muscle activity in response to this friction information [7].
Considering this, the aforementioned sensory stimulation provides
excellent feedback stimulation, indicating the direction of finger
movement. However, providing continuous feedback stimulation
corresponding to the kinetic friction that occurs between the finger
pads and the target object is difficult.
In recent years, a tactile discrimination compensation system has
been used for individuals with finger sensorimotor dysfunction toaddress this issue. This system has a sensing ability equivalent to thatof sensory receptors on the fingers. Several approaches involving
stimulators have been reported [23-26]. These reports suggest
that, when performing fine movements, the sensorimotor cortex
neurologically activates excitement and skilled movements, andimprovements have been reported. Therefore, the aforementioned
sensory feedback stimulation may be appropriate for individuals
with finger sensorimotor dysfunction.
However, to improve the implementation of fine finger movementsin actual movements in cervical spinal cord injury, two aspects
require verification. In addition to verifying the sensorimotor area
activation (early stage of motor learning) when fine movements
are performed, the late motor learning stage, a phase in which
the cognitive control necessary for sensorimotor information
processing is available and efficient, needs to be verified [27].
Therefore, spatially capturing brain activity areas and confirming
Volume 09; Issue 04

Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report. 9: 1950. DOI:10.29011/2574-7754.101950

whether there is a transition to late motor learning after the
implementation of an intervention is necessary. To do so, it isnecessary to assess the ability to process sensorimotor information,exert cognitive control, and capture electroencephalogram (EEG)
frequencies in the sensorimotor cortex, which are thought to reflect
these abilities [28,29]. Therefore, we examined a patient withcervical spinal cord injury and finger sensorimotor dysfunction
to determine whether an intervention using tactile discrimination
stimuli affects the motor learning process for performing finemovements. Efficacy was verified using brainwave frequency
analysis.
Case Presentation
Case Introduction
Three months before the intervention reported herein was
conducted, the patient fell off a bicycle into a 1.5 m-deep ditch,subsequently presenting with muscle weakness and sensory
dysfunction of the right finger as primary symptoms. The patient
was urgently transported to Hospital A, where cervical spinal
magnetic resonance imaging was performed. A C7 cervical spinal
cord injury and C6/7 cervical disc herniation were diagnosed(Figure 1A, B). The patient had no history of brain or cervicalspinal disease. The patient was able to get out of bed at Hospital Atransferred to a convalescent hospital, Hospital B, for rehabilitation.
The right-hand and finger rehabilitation approaches conducted at
Hospital B included range-of-motion training, muscle strength
training, and electrical stimulation therapy. The intervention was
conducted daily for 40 minutes. Three months after the injury,
the right-hand finger manual muscle test score improved from
3 to 4, and right-hand grip strength improved from 0 to 6 kg.
The numbness of the right index finger was measured using a
Numerical Rating Scale (NRS) ranging from 0 (not felt at all) to10 (felt extremely strongly) [25,26]. Although the score improved
from 9 to 4, numbness persisted. A Simple Test for Evaluating
Hand Function [30] that objectively assessed the ability of theupper limbs, including the fingers, to perform fine movements
was administered. The score improved from 86 to 93; however,the patient lost points when carrying a small pin. These findings
indicate a residual loss of dexterity in the right fingers.

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Ann Case Rep, an open access journal
ISSN: 2574-7754

Figure 1: Cervical spine MRI image taken during hospitalization
at Hospital B. A: Sagittal section at the C6/7 level. B: Horizontal
section at the C6/7 level showing compression of the right nerve
root. MRI, magnetic resonance imaging
Reason for selection
According to the Numbness NRS and Simple Test for Evaluating
Hand Function scores, right index finger numbness and decreased
fine motor skills persisted. Three months had passed since theonset of symptoms, meaning the optimal time for functional
recovery had also passed. This suggested that the patient may haveexperienced sensorimotor dysfunction. Therefore, according to
the patients’ wishes, the intervention described in this study wasadministered. This study was approved by the Kyoto Tachibana
University Ethics Review Committee (approval number, 23-27).
The purpose, content, and procedures of the study were explained
to the patients orally and in writing and informed consent was
obtained.
Intervention
Although real-time feedback devices have been developed forgross finger movements, no device is capable of detecting andproviding feedback on subtle differences in tactile modalities
in areas sensitive to tactile discrimination, such as the fingers.
Recently, the Yubi Recorder (Yubireco; Tech Gihan Co., Ltd.,
Kyoto, Japan) was developed to provide feedback. This device
provides vibrational information that corresponds to the tactile
modality of patients with sensorimotor disorders in the fingers
resulting from central nervous system differentiation disorders, andVolume 09; Issue 04

Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report. 9: 1950. DOI:10.29011/2574-7754.101950

interventional studies using this device have been reported [23-26].
The Yubireco device measures vibrational information by detecting
the vibrations within the skin that occur when touching an object
with the fingertips [31]. A vibration sensor was wrapped aroundthe distal interphalangeal joint of the index finger, and vibrational
information was presented via a vibrator by modulating the output
from the sensor to a frequency that humans could feel. Therefore,
in addition to synchronously matching the visual informationaccompanying finger movements, this approach provides real-time
feedback on the vibrational information associated with the robot
movements. In the present study, we used yubireco to conduct theintervention.
We aimed to compare the differences in intervention effects
between using and not using yubireco during an exercise task.
Moreover, we examined whether the length of the intervention
period for B caused changes in the learning performance during
skilled movements over time. As such, the intervention consistedof the first basic significance-level period A and the intervention
introduction period B. The intervention was conducted using an
ABB design for a period of 1–3 d. The intervention was performed
without the patient wearing the yubireco during the motor tasks. B
in periods 2 and 3 required moving the yubireco to the right index
finger during motor tasks. The distal interphalangeal joint of theindex finger was fitted. Each period lasted for one week for a totalof 21 days. The motor task was based on the method describedby Kitai et al. [25, 26] and consisted of using the right finger tostack the square building blocks used in the Box and Block Test[32] for 10 min, and discriminating between the five types ofsandpaper using the ventral part of the right index finger for 10
min. Participants were also asked to vertically insert a peg (25 mm
long, 3 mm in diameter) into a board with two rows of 25 holes,
each with their right finger (Peg Test) for 10 min.
Evaluations included pre- and post-evaluations, as well as
longitudinal evaluations. Pre- and post-evaluations were performed
before and after the start of periods 1–3 to assess sensory and motor
function and learning ability. During the longitudinal evaluation,neurophysiological, motor, and sensory function assessments were
performed daily.
The pre- and post-evaluation Pain Catastrophizing Scale (PCS)
evaluates the cognitive aspects of numbness as a sensory function
evaluation [33], converting all questions regarding pain items in
the questionnaire to numbness. The PCS consists of three subitems: rumination, when a person cannot release the numbness
from the mind; helplessness, when a person feels that they cannot
do anything to relieve the numbness; and magnification, when aperson perceives the numbness as stronger than it actually is; that
is, an enlarged view of the state is considered to occur. The test
consists of 14 items, and the evaluation is based on a 6-item scale(0 = not at all applicable to 5 = extremely applicable).
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ISSN: 2574-7754

Motor function was evaluated by measuring the grasping force
using a GFD50-A grasp force meter (Tec Gihan Co., Ltd., Kyoto,
Japan). This device measures the transportation time of thegrasping force meter and acceleration that occurs during an action.
The grasping force meter measured the generated vibration by
dividing it into three axis components: X, Y, and Z. To standardize
the movement distance of the grasping force meter, we used a
box-and-block test to evaluate finger dexterity [32]. In this study,
marks were placed at the midpoints of boxes 53.7 cm in widthand 25.4 cm high, which were used in the box and block tests.
The grasping force meter was set to move from the midpoint on
the left side to that on the right side. During the measurement,a 62 g weight was attached to the grasping force meter, and thetime and acceleration were measured three times. Hand and finger
activities of daily living and the quality of life Motor Activity
Log-14 (MAL-14) are useful tools for evaluating learning and theamount and quality of finger usage [34]. The MAL-14 is a 14-item
evaluation of upper limb use in real life. The upper Amount of Use(AOU) was evaluated using a 6-point scale (0 = not used at all to 5
= used as much as before injury), and the quality of movement wasevaluated using the QOM (0 = not able to do it at all to 5 = able doit as well as before injury). For each item of the MAL-14, the righthand fingers measured the sense of agency (SoA) NRS [25,26],
and the relationship between behavioural change and sense ofagency was evaluated. This sense of agency was measured using
the question, “How much do you feel that you are the one doing
your own exercise?” The NRS score was measured on a scale from0 (I do not feel it at all) to 10 (I feel it very strongly).
For longitudinal sensory function evaluation, the patient wasinterviewed once a day to administer the Numbness NRS to theright finger after completing motor tasks. For longitudinal motor
function evaluation, the Peg Test was used to evaluate finger
dexterity [35]. The Peg Test is an insertion test in which manyiron pins (Sakai Medical Co., Ltd., Tokyo, Japan) are inserted intoa board (Sakai Medical Co., Ltd.) with 25 holes arranged in two
vertical rows within 30 s. Measurements were performed twice
daily after the motor task. Neurophysiological evaluations wereconducted after completion of the motor task.
EEG activity during the Peg Test was measured daily for 1 min.
EEG measurements were obtained while the participants wereseated in a relaxed and quiet environment. These measurements
were performed once without the patient wearing the yubirecousing a portable electroencephalograph (StEEG; Altaire) (Creact
Co., Ltd.,Tokyo, Japan). Based on the international 10–20 method,the electroencephalogram was measured at eight sites, namely
Fp1, Fp2, T7, T8, O1, O2, Fz, and Pz, using both earlobes asreference electrodes. The bandpass filter was set to 4–30 Hz, andthe sampling frequency was set to 1,000 Hz.

Volume 09; Issue 04

Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report. 9: 1950. DOI:10.29011/2574-7754.101950

Analysis Method
For the pre- and post-evaluations, the PCS was used to compare
the scores of the sub-items and the total score of the sub-items
between periods. The average values and standard deviations of
the three tests were calculated during the evaluation of the grasping
force using the total sum. Acceleration was evaluated by measuring
the X-, Y-, and Z-axes, and calculating the average and standard
deviation of the composite value (3-axis composite value) of thevalues (effective values) multiplied by the coefficients transmitted
to the fingers at each frequency (3-axis composite value [m/s2]).
The values obtained by multiplying “a” with the coefficientstransmitted to the fingers for each frequency of the three axes wereset as ax, ay, and az, and the obtained data were input into thefollowing formula: a=√ax2+ay2+az2.
The meter task was set as the average time required to complete
the grasping force. The average value of the 3-axis composite wascalculated three times, and the average value and standard deviation
were calculated from the summation. In this task, the grasping
force meter must be moved quickly to shorten task completion
time. However, when the meter moved rapidly, the acceleration of
the meter and fingers increased, thereby increasing the variationin the 3-axis composite value. Therefore, to perform the taskquickly, the acceleration must be adjusted to avoid a decrease in
the grasping force of the fingers. This control is achieved using afinger pad. Thus, the shorter the average time of the grasping force
task, the more difficult it is to control the acceleration generated
by the grasping dynamometer and fingers within the finger pads.
This indicates that the upper limbs moved smoothly. The MAL14 AOU and QOM were scored by dividing the total score on a
6-point scale from 0 to 5 by the number of items. The scores werecompared between periods.
The Longitudinal evaluation was conducted as follows: Tau-U was
calculated using the Numbness NRS score and the maximum valueof the Peg Test. Tau U calculations were performed to determine
the effect sizes of the statistical indices representing the size ofthe effect. Tau-U is characterized by the ability to correct baseline
trends by combining the non-overlap between periods and trends
in the intervention phase [36]. The Tau-U values were obtained for
A versus B in period 1, A versus B in period 2, and B in period 2
versus B in period 3. The effect judgment of the results obtained
when the Tau-U value is 0~0.20 is that the change is assumed tobe small, when the value is 0.20–0.60, the change is assumed tobe moderate, when the value is 0.60–0.80, the change is assumed
to be large, and when the value is 0.80–1, the change is assumed
to be very large [37]. Tau-U analysis was conducted using the web
application software single-case research web-based calculators
for SCR analysis (version 2.0) [38].
Independent Component Analysis (ICA) was performed to preprocess the EEG data. ICA represents a multidimensional random
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Ann Case Rep, an open access journal
ISSN: 2574-7754

vector as a linear combination of non-Gaussian random variables
that are as statistically independent as possible [39]. MATLAB(Matrix Laboratory) version R2023b with the EEGLAB toolbox[40] was used to implement the ICA. Infomax algorithms were
implemented in EEGLAB [41], and their independent components
were extracted from the EEG data. From the components separated
by the ICA, the signal before mixing was estimated under theassumption that it was a linear sum of statistically independent
components to extract clean EEG data. The noise-processed data
were subjected to coherence analysis between the FZ and PZ.
Furthermore, a custom script created in MATLAB was used to
extract the average coherence values in the theta- and mu-wave
bands. The theta- and mu-wave coherence values obtained for eachperiod were summed, and the average and standard deviations
were determined. The values were compared for each period.
Results
Except for the p-values, the data obtained in this study wereexpressed to two decimal places.
Regarding the evaluation of sensory function, the Numbness NRSscores were 3.71 ± 0.49 for A, 1.00 ± 0.58 and B in period 2, and0.14 ± 0.38 for B in period 3. When comparing A and B in period
2, a Tau-U1 (very large change) was observed for B in period 2.
Similarly, when comparing A and B in period 3, a Tau-U1 (verylarge change) was observed in B in period 3. A comparison of B
in period 2 and B in period 3 indicated a change in Tau-U0.83(a very large change) for B in period 3 (Figure 2; Table 1). The
PCS score was 14 points for A, including 13 points for rumination,
1 point for helplessness, and 0 point for magnification. In period
2, the PCS scores improved to 7, 0, and 0 points for rumination,
helplessness, and magnification, respectively, whereas in period 3,
the PCS score was 0 (Table 2).
The assessment of motor function yielded the following results:
The Peg Test scores were 12.00 ± 1.00 for A, 15.29 ± 0.76 for B inperiod 2, and 16.14 ± 0.69 for B in period 3. Comparing A and B
in period 2, a Tau-U1 (very large change) was observed in period
2. When comparing periods A and B in period 3, Tau Tau-U1 (avery large change) was observed in period 3. A comparison of B inperiods 2 and 3 showed a change of Tau-U0.67 (large change in)for B in period 3 (Figure 3; Table 3). In the grasping force meter
evaluation, the task execution time was 4.50 ± 1.65 in the initial
evaluation, 2.30 ± 0.78 for A, 2.07 ± 0.46 for B in period 2, and1.60 ± 0.10 for B in period 3. Compared to A, B had shorter task
performance times. The triaxial composite values were 8.06 ± 2.96
for the initial evaluation, 9.37 ± 0.16 for A, 7.73 ± 2.83 for B inperiod 2, and 9.10 ± 0.09 for B in period 3 (Figure 4A, B).
For MAL, the AOU, QOM, and SoA scores were 4.21, 4.21, and122, respectively. In period 2, the AOU, QOM, and SoA scores forgroup B improved to 4.71, 4.71, and 132 points, respectively, andVolume 09; Issue 04

Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report. 9: 1950. DOI:10.29011/2574-7754.101950

they further improved to 4.86, 4.86, and 136 points, respectively, in period 3 (Table 2).
The theta wave coherence values in the Fz–Pz region for A were 0.57 ± 0.19, and for B they were 0.56 ± 0.19 in period 2 and 0.46 ± 0.14
in period 3. The mu wave coherence values in the Fz–Pz region for A were 0.57 ± 0.19, and for B they were 0.57 ± 0.20 in period 2 and0.45 ± 0.10 in period 3 (Figure 5A, B; Table 4).

Figure 2: Numbness NRS.

Table 1: Numbness NRS results and Tau-U for each period. S, number of non-overlapping data points in the baseline and intervention
periods; VARs, variance; Z, standard score; p-value, probability of realized value; CI90%, 90% confidence interval.

Table 2: Before and after evaluation. Pain Catastrophizing Scale: PCS, Motor Activity Log-14: MAL-14, Amount of Use: AOU, Qualityof Movement: QOM, Sense of Agency: SoA.

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Ann Case Rep, an open access journal
ISSN: 2574-7754

Volume 09; Issue 04

Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report. 9: 1950. DOI:10.29011/2574-7754.101950

Figure 3: Peg test.

Table 3: Peg test results and Tau-U for each period.

Figure 4: Grasping force measurement. A: Time required for the grasping force task; B: 3-axis composite value; * unit: m/s2

Figure 5: Fz-Pz coherence. A: θ wave coherence value, B: μ wave coherence value.
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Ann Case Rep, an open access journal
ISSN: 2574-7754

Volume 09; Issue 04

Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report. 9: 1950. DOI:10.29011/2574-7754.101950

Table 4: EEG frequency analysis results for each period.
Discussion
Herein, we present the case of a patient who fell off his bicycle
approximately 3 months previously, incurring a cervical cord injury;
rehabilitation was performed for numbness and loss of dexterity inthe right hand and fingers. However, the numbness persisted in his
right hand, causing motor dysfunction. Sensorimotor dysfunctionin the right finger was suspected. To improve the right-hand finger
sensorimotor function, in addition to synchronously matching thevisual information associated with finger movements, an approach
using the friction information generated when the fingers touch
an object was implemented. This approach uses the real-time
vibrational information feedback provided by a Yubireco device.
We used EEG frequency analysis to verify whether the ABB
design affects the motor learning process during fine movements.
Sensory function was evaluated using the Numbness NRS to
calculate Tau-U. Compared with group A, the largest change wasobserved in group B during period 3. Numbness in the fingers of theright hand disappeared after B in period 3. When the sensorimotor
area is activated through active movement, the brain eliminates
unnecessary information for motor control and inputs only thenecessary sensory information [42]. In this case, the coherence
value of the front parietal region was the greatest for B in period 3,
showing decay. The decay of mu waves enhances the sensorimotor
processing ability during movement execution [28]. Therefore,
using the Yubireco device may have enabled the suppression of
unnecessary numbness during fine movements, because the patient
could perform the movements more efficiently. Thereby The PCS
score, which assesses the cognitive aspect of numbness, improved
from 14 to 0 points as the numbness during exercise improved.
Motor function evaluation, assessed using the Peg Test, was basedon the results of the Tau-U analysis. The comparison of the resultsfor A and B showed that the largest change was observed for B
during Period 3. In terms of the grasping force, the time required
to complete the task was shorter and varied less for B in Period 3
than for A. When the ability to process sensorimotor informationis strengthened, the sensory information at the fingertips predicts
strengthened abilities, and the corresponding fine movements ofthe fingers become possible [43,44]. In the current case, the mu8
Ann Case Rep, an open access journal
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wave coherence value of the Fz–Pz region [28], which enhances
the sensory-motor information processing ability, showed
the greatest decay in period 3. Therefore, after two weeks ofintervention with yubireco, predicting the frictional information of
the hands and fingers was possible, which may have enabled thepatient to perform the fine movement task quickly. Additionally,
theta waves are attenuated when the cognitive control necessary
for sensorimotor information processing is efficiently performed(transitioning to the late stage of motor learning) [29]. In thecurrent case, the theta-wave coherence showed the greatest decay
for B in period 3 in the Fz–Pz region. This suggests that cognitive
control during the skilled movements in Period 3 might have been
more efficient in the frontoparietal region.
The AOU score for the MAL-14 showed an increasing trend from
4.21 to 4.86 points for B in period 3. In the AOU, the minimal
clinically important difference (MCID) which can be interpreted
as a beneficial change in the outcome when an intervention is
implemented, was defined as 0.5 points [45]. In the present case,
the MCID of the AOU was exceeded, suggesting that the frequency
of finger use with the right hand improved in daily life. Comparedwith A, the QOM score showed an improving trend from 4.07 to
4.86 points for B in Period 3. Several factors may have contributed
to the improvements in the AOU and QOM scores. If a person
continues to fail in the intended movement because of finger
sensorimotor dysfunction, their ability to learn that movement
decreases [12]. The patient may also have right-hand finger
sensory-motor dysfunction, which results in poor quality during
right-hand finger movements and learning not to use the fingers.
Behavioural changes to improve learned non-use require a senseof agency at the sensory level, where sensory feedback temporally
matches motor predictions. Therefore, generating this information
is important. In addition, motor learning occurs by generating a
sense of motor subjectivity at the cognitive level, which allows therecall of the temporal coincidence of motor and sensory feedback[46]. Feedback stimulation, which corresponds to the friction
information during object manipulation, is also important [47]. In
this case, we considered that exercises using real-time feedback
stimulation corresponding to friction information improved thesense of agency during the right-hand finger movements. We also
consider that improving the sense of agency may improve thequality and quantity of use of the right-hand fingers. However,the MCID of the QOM score was 1.1 points [48], which is lessthan the MCID of the QOM. This was because the QOM scorein this case exceeded four points at the time of implementing theintervention, making an intervention with a score higher than one
point on the MCID difficult. The grip strength is involved in motor
control during fine movements [49]. The fact that the patient’s grip
strength was only 6 kg may have been another factor contributing
to the QOM not improving to the extent that it exceeded the MCID
score.
Volume 09; Issue 04

Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report. 9: 1950. DOI:10.29011/2574-7754.101950

In this case, the results of the neurophysiological evaluations
showed that the theta and mu wave coherence values in the Fz–
Pz region were the lowest for B in period 3. Therefore, motor
learning during fine movements may have moved to a later stage
in period 3. Skilled movements were performed more smoothly
during Period 3 than during Period 1. In contrast, no difference
was observed in the numerical values of the Fz–Pz theta and mu
waves between A and B during Period 2. Thus, we considered that
although the intervention using yubireco affected numbness of thefingers and motor function after 1 week of intervention, 2 weeks
of intervention were required to affect brain wave frequency. The
results of this study suggest the possibility of early improvement
in finger sensorimotor function in patients with hand sensorimotor
dysfunction after cervical cord injury.
This study has some limitations. First, the effects of sensory
feedback devices cannot be separated from those of sustained
exercise. Second, the cortical activation patterns recorded by EEG
differ from those of cognitive and motor stimuli associated withintensive interventions and cannot be attributed to the specificeffects of new rehabilitation techniques.
Conclusion
In the present case, the intervention was conducted using feedback
through sensory compensation, a treatment strategy developed by
Sharma et al. [16] as the basis for treating neurological disorders.
These results suggest that yubireco mimics the motor learning
process. We suggest that the recovery mechanism for finger
sensorimotor dysfunction requires processing of active and realtime sensorimotor information during movement execution.
To date, a recovery time of at least 8 weeks of intervention
is required, hindering the recovery of finger motor function
caused by injury to the cervical cord [50]. Medical expenses for
hospitalization and rehabilitation in cases of cervical spinal cord
injury are approximately eight times greater than those in cases
without injury [51]. Improving the quality of rehabilitation andshortening the length of hospitalization are urgent issues to reduce
the socioeconomic burden on patients and their families. This
study investigated the effects of finger sensorimotor dysfunction,a factor that lowers finger motor function. Using Yubireco, an
improvement in fine motor skills was observed within 2 weeks
of implementing the intervention. Thus, a compensatory real-time
feedback approach for tactile sensory discrimination in cases offinger sensorimotor dysfunction after cervical spinal cord injury,
reduces the duration of hospitalization and the number of hospital
visits. In future, we plan to increase the number of cases and target
diseases. We would also like to verify the effectiveness of this tool
statistically.
Disclosures
Acknowledgments: We would like to express our sincere gratitude
9
Ann Case Rep, an open access journal
ISSN: 2574-7754

to the male participants who understood the purpose of this study
and were willing to work together with us. Thank you very much.
Institutional Review Board Statement: The study was conductedin accordance with the guidelines of the Declaration of Helsinki
and approved by the Kyoto Tachibana University Ethics Review
Board (Protocol Code 23-27; Date of Approval July 21, 2023).
Informed Consent Statement: Informed consent was obtained
from all participants involved in the study.
Conflict of Interest: The authors declare no conflicts of interest.
The sponsors played no role in the design, execution, interpretation,
or writing of this study.
Funding: This research was funded by the Kyoto Tachibana
University Research Fund (no grant number).
Author Contributions: Conceptualization, K. K. and T. K.;
methodology, K. K. and T. K.; software, K. K.; validation, K. K., D.
I., and T. K.; formal analysis, K. K., S. M., and T. K.; investigation,
K. K.; resources, K. K. and T. K.; data curation, K. K.; writing—original draft preparation, K. K.; writing—review and editing, K.
K. K. and T. K.; visualization, K. K.; supervision, T. K.; project
administration, T. K. All authors have read and agreed to publish
this version of the manuscript.
Data Availability Statement: The data supporting the findings ofthis study are available from the corresponding author, T. K., upon
reasonable request.
References
1.

Petersen JA, Spiess M, Curt A, Weidner N, Rupp R, et al. (2017)
Upper Limb Recovery in Spinal Cord Injury: Involvement of Central
and Peripheral Motor Pathways. Neurorehabil Neural Repair. 31: 432441.

2.

Dai L, Jia L. (1997) Acute Central Cervical Cord Injury Presenting With
Only Upper Extremity Involvement. Int Orthop. 21: 380-382.

3.

Simpson LA, Eng JJ, Hsieh JT, Wolfe DL; Spinal Cord Injury
Rehabilitation Evidence Scire Research Team. (2012) The Healthand Life Priorities of Individuals With Spinal Cord Injury: A Systematic
Review. J Neurotrauma. 29: 1548-1555.

4.

Peckham P, Keith MW, Kilgore K, Grill JH, Wuolle KS, et al. (2001)
Efficacy of an Implanted Neuroprosthesis for Restoring Hand Grasp in
Tetraplegia: A Multicenter Study. Arch Phys Med Rehabil. 1380-1388.

5.

Jiang Z, Davies B, Zipser C, Margetis K, Martin A, et al. (2023) The
Frequency of Symptoms in Cases With a Diagnosis of Degenerative
Cervical Myelopathy: Results of a Scoping Review. Global Spine
J.21925682231210468.

6.

Divi SN, Schroeder GD, Mangan JJ, Tadley M, Ramey WL, et al.
(2019) Management of Acute Traumatic Central Cord Syndrome: A
Narrative Review. Global Spine J. 9: 89S–97S.

7.

Sarlegna FR, Sainburg RL. (2009) The Roles of Vision and
Proprioception in the Planning of Reaching Movements. Adv Exp Med
Biol. 629: 317-335.

8.

Doyle S, Bennett S, Fasoli SE, McKenna KT. (2010) Interventionsfor Sensory Impairment in the Upper Limb After Stroke. Cochrane
Database Syst Rev. 2010: CD006331.
Volume 09; Issue 04

Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report. 9: 1950. DOI:10.29011/2574-7754.101950
9.

Maier M, Ballester BR, Verschure PFMJ. (2019) Principles of
Neurorehabilitation After Stroke Based on Motor Learning and Brain
Plasticity Mechanisms. Front Syst Neurosci. 13: 74.

10. Cha J, Heng C, Reinkensmeyer DJ, Roy RR, Edgerton VR, De
Leon RD. (2007) Locomotor Ability in Spinal Rats is Dependent on
the Amount of Activity Imposed on the Hindlimbs During Treadmill
Training. J Neurotrauma. 24: 1000-1012.
11. Yang YK, Lin CY, Chen PH, Jhou HJ. (2023) Timing and Dose ofConstraint-Induced Movement Therapy after Stroke: A Systematic
Review and Meta-Regression. J Clin Med. 12: 2267.
12. Taub E, Uswatte G, Mark V, Morris D. (2006). The Learned Nonuse
Phenomenon: Implications for Rehabilitation. Europa medicophysica.
42: 241-256.
13. Corbetta D, Sirtori V, Castellini G, Moja L, Gatti R. (2015) ConstraintInduced Movement Therapy for Upper Extremities in People With
Stroke. Cochrane Database Syst Rev. 2015: CD004433.
14. Hubbard IJ, Parsons MW, Neilson C, Carey LM. (2009) Task-SpecificTraining: Evidence for and Translation to Clinical Practice. Occup Ther
Int.16: 175-189.
15. David N, Newen A, Vogeley K. (2008) The “Sense of Agency” and its
Underlying Cognitive and Neural Mechanisms. Conscious Cogn. 17:
523-534.
16. Sharma N, Cohen LG. (2012) Recovery of Motor Function After Stroke.
Dev Psychobiol. 54: 254-262.
17. Dohle C, Kleiser R, Seitz RJ, Freund HJ. (2004) Body Scheme Gates
Visual Processing. J Neurophysiol. 91: 2376-2379.
18. Gygax MJ, Schneider P, Newman CJ. (2011) Mirror Therapy in Children
with Hemiplegia: A Pilot Study. Dev Med Child Neurol. 53: 473-476.
19. Ramachandran VS, Altschuler EL. (2009) The Use of Visual Feedback,in Particular Mirror Visual Feedback, in Restoring Brain Function.
Brain. 132: 1693-1710.
20. Hu, X.L., Tong R, Ho NSK, Xue J, Rong W,et al. “Wrist rehabilitation
assisted by an electromyography-driven neuromuscular electricalstimulation robot after stroke.” Neurorehabil Neural Repair 29 (2015):
767-776.
21. Biasiucci A, Leeb R, Iturrate I, Perdikis S, Al-Khodairy A, et al. (2018)
Brain-Actuated Functional Electrical Stimulation Elicits Lasting Arm
Motor Recovery After Stroke. Nat Commun. 9: 2421.
22. Rosati G, Rodà A, Avanzini F, Masiero S (2013) On the Role of Auditory
Feedback in Robot-Assisted Movement Training After Stroke: Reviewof the Literature. Comput Intell Neurosci. 2013: 586138.
23. Awaji A, Fuchigami T, Ogata R, Morioka S(2023) Effects of VibrationBased Generation of Timing of Tactile Perception on Upper Limb
Function After Stroke: A Case Study. Cureus. 15.
24. Kodama T, Kitai K. (2023) Clinical Usefulness of Real-time Sensory
Compensation Feedback Training on Sensorimotor Dysfunction After
Stroke. 25-50.

28. de Souza RFL, Mendes TMAS, Lima LABA, Brandão DS, Laplagne
DA, et al (2022) Effect of the Menstrual Cycle on Electroencephalogram
Alpha and Beta Bands During Motor Imagery and Action Observation.
Front Hum Neurosci. 16: 878887.
29. Helfrich RF, Breska A, Knight RT. (2019) Neural Entrainment andNetwork Resonance in Support of Top-Down Guided Attention. Curr
Opin Psychol. 29: 82-89.
30. Kaneko T, Muraki T. (1990) Development and Standardization of Hand
Function Test. Bull Allied Med Sci Kobe. 6: 49-54.
31. Tanaka Y, Ueda Y, Sano A. (2016) Roughness Evaluation by Wearable
Tactile Sensor Utilizing Human Active Sensing. Mech Eng J. 3: 1-12.
32. Mathiowetz V, Volland G, Kashman N, Weber K. (1985) Adult norms
for the Box and Block Test of manual dexterity. Am J Occup Ther. 39：386-391.
33. Sullivan MJL, Bishop SR, Pivik J. (1995) The Pain Catastrophizing
Scale: Development and Validation. Psychol Assess. 7: 524-532.
34. Uswatte G, Taub E, Morris D, Vignolo M, McCulloh K. (2005) Reliability
and Validity of the Upper-Extremity Motor Activity Log-14 for Measuring
Real-World Arm Use. Stroke. 36: 2493-2496.
35. Irie K, Iseki H, Okamoto K, Nishimura S, Kagechika K (2020)
Introduction of the Purdue Pegboard Test for fine assessment ofseverity of cervical myelopathy before and after surgery. J Phys Ther
Sci. 32: 210-214.
36. Parker RI, Vannest KJ, Davis JL, Sauber SB. (2011) Combining
Nonoverlap and Trend for Single‒Case Research: Tau–U. Behav
Ther. 42: 284-299.
37. Ninci J, Vannest KJ, Willson V, Zhang N. (2015) Interrater Agreement
Between Visual Analysts of Single-Case Data: A Meta-Analysis. Behav
Modif. 39: 510-541.
38. Vannest, K.J., Parker, R.I., Gonen, O., & Adiguzel, T. (2016). Single
Case Research: web-based calculators for SCR analysis. (Version2.0) [Web-based application]. College Station, TX: Texas A&M;
University. Retrieved Sunday 24th March 2024. Available fromsinglecaseresearch.org
39. Hyvärinen A, Oja E. (2000) Independent Component Analysis:
Algorithms and Applications. Neural Networks. 13: 411-430.
40. Delorme A, Makeig S. (2004) EEGLAB: An Open Source Toolbox
for Analysis of Single-Trial EEG Dynamics Including Independent
Component Analysis. J Neurosci Methods. 134: 9-21.
41. Bell AJ, Sejnowski TJ. (1995) An Information-Maximization Approachto Blind Separation and Blind Deconvolution. Neural Computation. 7:1129-1159.
42. Yamashita T, Pala A, Pedrido L, Kremer Y, Welker E, Petersen CCH(2013) Membrane Potential Dynamics of Neocortical Projection
Neurons Driving Target-Specific Signals. Neuron. 80: 1477–1490.
43. Limanowski J. (2022) Precision Control for a Flexible Body
Representation. Neurosci Biobehav Rev. 134: 104401.

25. Kitai K, Ueda T, Yamauchi R, Mizushima Y (2022) Effectivenessof Sensory Compensation Approach for Hand Sensory-Motor
Dysfunction Following Central Cervical Spinal Cord Injury. Int J Phys
Med Rehabil. 10: 649.

44. Smit M, Brummelman JTH, Keizer A, van der Smagt MJ, Dijkerman
HC, et al (2018) Body Ownership and the Absence of Touch:
Approaching the Rubber Hand Inside and Outside Peri-Hand Space.
Exp Brain Res. 236: 3251-3265.

26. Kitai K, Odagiri M, Yamauchi R, Kodama T. (2021) Evaluation ofIntervention Effectiveness of Sensory Compensatory Training With
Tactile Discrimination Feedback on Sensorimotor Dysfunction of theHand After Stroke. Brain Sci. 11: 1314.

45. van der Lee JH, Wagenaar RC, Lankhorst GJ, Vogelaar TW, et al.
(1999) Forced Use of the Upper Extremity in Chronic Stroke Cases:
Results From a Single-Blind Randomized Clinical Trial. Stroke. 30:
2369-2375.

27. Leech KA, Roemmich RT, Gordon J, Reisman DS, Cherry-Allen KN.
(2022) Updates in Motor Learning: Implications for Physical Therapist
Practice and Education. Phys Ther. 102: pzab250.

46. Synofzik M, Vosgerau G, Newen A. (2008) Beyond the Comparator
Model: A Multifactorial Two-Step Account of Agency. Conscious Cogn.
17: 219-239.

10
Ann Case Rep, an open access journal
ISSN: 2574-7754

Volume 09; Issue 04

Citation: Kitai K, Ito D, Murata S, Katayama O, Kodama T (2024) Verifying the Efficacy of a Tactile Perceptual Discrimination Stimulation Approach for Individuals
with Finger Sensorimotor Dysfunction: A Case Report and Literature Review. Ann Case Report. 9: 1950. DOI:10.29011/2574-7754.101950

47. Zangrandi A, D’Alonzo M, Cipriani C, Di Pino G. (2021) Neurophysiology
of Slip Sensation and Grip Reaction: Insights for Hand Prosthesis
Control of Slippage. J Neurophysiol. 126: 477-492.

50. Bertels N, Seelen H, Dembele J, Spooren A. (2023) Essential Training
Variables of Arm-Hand Training in People With Cervical Spinal Cord
Injury: A Systematic Review. J Rehabil Med. 55: jrm7147.

48. Lang CE, Edwards DF, Birkenmeier RL, Dromerick AW. (2008)
Estimating Minimal Clinically Important Differences of Upper-Extremity
Measures Early After Stroke. Arch Phys Med Rehabi. 89: 1693-1700.

51. Chan BC, Cadarette SM, Wodchis WP, Krahn MD, Mittmann N.
(2019) The Lifetime Cost of Spinal Cord Injury in Ontario, Canada:
A Population-Based Study From the Perspective of the Public HealthCare Payer. J Spinal Cord Med. 42: 184-193.

49. Martin JA, Ramsay J, Hughes C, Peters DM, Edwards MG. (2015)
Age and Grip Strength Predict Hand Dexterity in Adults. PLoS One.
10: e0117598.

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ISSN: 2574-7754

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