High-sensitivity acceleration sensor detecting micro-mechanomyogram and deep learning approach for parkinson's disease classification.

High-sensitivity acceleration sensors have been independently developed by our research group to detect vibrations that are > 10 dB smaller than those detected by conventional commercial sensors. This study is the first to measure high-frequency micro-vibrations in muscle fibers, termed micro-mechanomyogram (MMG) in patients with Parkinson's disease (PwPD) using a high-sensitivity acceleration sensor. We specifically measured the extensor pollicis brevis muscle at the base of the thumb in PwPD and healthy controls (HC) and detected not only low-frequency MMG (< 15 Hz) but also micro-MMG (≥ 15 Hz), which was preciously undetectable using commercial acceleration sensors. Analysis revealed remarkable differences in the frequency characteristics of micro-MMG between PwPD and HC. Specifically, during muscle power output, the low-frequency MMG energy was greater in PwPD than in HC, while the micro-MMG energy was smaller in PwPD compared to HC. These results suggest that micro-MMG detected by the high-sensitivity acceleration sensor provides crucial information for distinguishing between PwPD and HC. Moreover, a deep learning model trained on both low-frequency MMG and micro-MMG achieved a high accuracy (92.19%) in classifying PwPD and HC, demonstrating the potential for a diagnostic system for PwPD using micro-MMG.

Effect of time delay on performance and timing control in dyadic rhythm coordination using finger tapping.

In musical ensembles, people synchronise with each other despite the presence of time delays such as those related to sound transmission. However, the ways in which time delays in synchronisation are overcome remain unclear. This study aimed to investigate the basic characteristics and mechanism of synchronisation with time delays using a dyadic synchronisation-continuation finger-tapping task with time delays ranging from 0 to 240 ms. The results reveal that synchronisation performance improved under time delays of 40-160 ms compared with in the other conditions. This tolerance to the time delay could have been because such a delay allowed both participants in each pair to tap before receiving the stimuli from their partner, as seen in synchronisation with a constant-tempo metronome. In addition, the dependency of the timing control on the partner's previous inter-tap interval decreased at a time delay of 80 ms, relating to the fact that the acceleration and deceleration of the tapping tempo reduced under certain time delays, while the synchronisation performance improved. Uncertainty in the timing of the partner's stimulus could induce greater anticipatory responses, making it possible to tolerate longer time delays in dyadic finger-tapping tasks.

Classification of mild Parkinson's disease: data augmentation of time-series gait data obtained via inertial measurement units.

Data-augmentation methods have emerged as a viable approach for improving the state-of-the-art performances for classifying mild Parkinson's disease using deep learning with time-series data from an inertial measurement unit, considering the limited amount of training datasets available in the medical field. This study investigated effective data-augmentation methods to classify mild Parkinson's disease and healthy participants with deep learning using a time-series gait dataset recorded via a shank-worn inertial measurement unit. Four magnitude-domain-transformation and three time-domain-transformation data-augmentation methods, and four methods involving mixtures of the aforementioned methods were applied to a representative convolutional neural network for the classification, and their performances were compared. In terms of data-augmentation, compared with baseline classification accuracy without data-augmentation, the magnitude-domain transformation performed better than the time-domain transformation and mixed-data augmentation. In the magnitude-domain transformation, the rotation method significantly contributed to the best performance improvement, yielding accuracy and F1-score improvements of 5.5 and 5.9%, respectively. The augmented data could be varied while maintaining the features of the time-series data obtained via the sensor for detecting mild Parkinson's in gait; this data attribute may have caused the aforementioned trend. Notably, the selection of appropriate data extensions will help improve the classification performance for mild Parkinson's disease.

Preceding and trailing role-taking in dyad synchronization using finger tapping.

In ensembles, people synchronize the timings of their movements with those of others. Players sometimes take on preceding and trailing roles, whereby one's beat is either slightly earlier or slightly later than that of another. In this study, we aimed to clarify whether the division of preceding and trailing roles occurs in simple rhythmic coordination among non-musicians. Additionally, we investigated the temporal dependencies between these roles. We conducted a synchronous-continuous tapping task involving pairs of people, whereby pairs of participants first tapped to synchronize with a metronome. After the metronome stopped, the participants synchronized their taps to their partners' tap timings, which were presented as auditory stimuli. Except in one trial, the pairs involved participants taking on preceding and trailing roles. Compared to the participants taking on the trailing role, those taking on the preceding role demonstrated enhanced phase-correction responses, while those taking on the trailing role significantly adapted their tempos to match those of their partners. As a result, people spontaneously divided into preceding and trailing roles. The preceding participants tended to reduce asynchronies, while the trailing participants tended to match their tempo to their partners'.

Three-dimensional foot trajectory in female patients with end-stage hip osteoarthritis during walking.

Osteoarthritis (OA) is a risk factor for falls. To decrease the fall risk, it is important to evaluate the detailed features of the gait of patients with OA. This study aimed to investigate the spatio-temporal parameters of gait in patients with end-stage hip OA, especially foot trajectory. We measured normal speed gait in patients with hip OA and in healthy controls (HCs) using inertial measurement units attached to shanks. The stride lengths in the affected and unaffected sides in the patients with hip OA were shorter than those in the HCs, but the position of maximum foot clearance was not significantly different between the two groups. The patients with hip OA compensated the position of maximum foot clearance to avoid fall risk. The horizontal plane foot trajectory in patients with hip OA suggests that the lateral bending of the trunk during walking, which is frequently seen in them, was a result of the lateral distance at swing down being located significantly more medially on the unaffected side than on the affected side. Herein, a new gait parameter of lateral distance at swing was discovered by a detailed evaluation of three-dimensional foot trajectory of female patients with end-stage hip OA.

Foot Trajectory Features in Gait of Parkinson's Disease Patients.

Parkinson's disease (PD) is a progressive neurological disorder characterized by movement disorders, such as gait instability. This study investigated whether certain spatial features of foot trajectory are characteristic of patients with PD. The foot trajectory of patients with mild and advanced PD in on-state and healthy older and young individuals was estimated from acceleration and angular velocity measured by inertial measurement units placed on the subject's shanks, just above the ankles. We selected six spatial variables in the foot trajectory: forward and vertical displacements from heel strike to toe-off, maximum clearance, and change in supporting leg (F1 to F3 and V1 to V3, respectively). Healthy young individuals had the greatest F2 and F3 values, followed by healthy older individuals, and then mild PD patients. Conversely, the vertical displacements of mild PD patients were larger than the healthy older individuals. Still, those of healthy older individuals were smaller than the healthy young individuals except for V3. All six displacements of the advanced PD patients were smaller than the mild PD patients. To investigate features in foot trajectories in detail, a principal components analysis and soft-margin kernel support vector machine was used in machine learning. The accuracy in distinguishing between mild PD patients and healthy older individuals and between mild and advanced PD patients was 96.3 and 84.2%, respectively. The vertical and forward displacements in the foot trajectory was the main contributor. These results reveal that large vertical displacements and small forward ones characterize mild and advanced PD patients, respectively.

Estimation of stride-by-stride spatial gait parameters using inertial measurement unit attached to the shank with inverted pendulum model.

Inertial measurement unit (IMU)-based gait analysis systems have become popular in clinical environments because of their low cost and quantitative measurement capability. When a shank is selected as the IMU mounting position, an inverted pendulum model (IPM) can accurately estimate its spatial gait parameters. However, the stride-by-stride estimation of gait parameters using one IMU on each shank and the IPMs has not been validated. This study validated a spatial gait parameter estimation method using a shank-based IMU system. Spatial parameters were estimated via the double integration of the linear acceleration transformed by the IMU orientation information. To reduce the integral drift error, an IPM, applied with a linear error model, was introduced at the mid-stance to estimate the update velocity. the gait data of 16 healthy participants that walked normally and slowly were used. The results were validated by comparison with those extracted from an optical motion-capture system; the results showed strong correlation ([Formula: see text]) and good agreement with the gait metrics (stride length, stride velocity, and shank vertical displacement). In addition, the biases of the stride length and stride velocity extracted using the motion capture system were smaller in the IPM than those in the previous method using the zero-velocity-update. The error variabilities of the gait metrics were smaller in the IPM than those in the previous method. These results indicated that the reconstructed shank trajectory achieved a greater accuracy and precision than that of previous methods. This was attributed to the IPM, which demonstrates that shank-based IMU systems with IPMs can accurately reflect many spatial gait parameters including stride velocity.

Effects of a partner's tap intervals on an individual's timing control increase in slow-tempo dyad synchronisation using finger-tapping.

In musical ensembles, musicians synchronise their movements with other members of the ensemble at various tempos. This study aims to investigate the extent of tempo dependency of own and partner's timing information on rhythm production. We conducted a dyad synchronisation-continuous finger-tapping task. First, two participants synchronised with the same auditory metronome at various tempos. Subsequently, after stopping the metronome, the participants maintained the tempo with the presentation of the partner's tap timing via auditory signals. This task was conducted in six metronome tempo conditions at 700 to 3,200 ms in 500 ms step. It was found that the partner's previous inter-tap intervals increased as the metronome tempo decreased. The effects of own previous inter-tap intervals and synchronisation errors between own and the partner's tap timing did not depend on the metronome tempo. Therefore, timing control in dyad synchronisation was affected by the partner's tempo more strongly in slow than fast tempos. This strong effect of the partner in slow-tempo rhythm synchronisation could be due to stronger attention to the partner's movement timing in slower tempos than in fast tempos.

Synchronized Tactile Stimulation on Upper Limbs Using a Wearable Robot for Gait Assistance in Patients With Parkinson's Disease.

This study aimed to investigate whether using a wearable robot applying interactive rhythmic stimulation on the upper limbs of patients with Parkinson's disease (PD) could affect their gait. The wearable robot presented tactile stimuli on the patients' upper limbs, which was mutually synchronized with the swing of their upper limbs. We conducted an evaluation experiment with PD patients (n = 30, Modified Hoehn-Yahr = 1-3, on-state) to investigate the assistance effect by the robot and the immediate after-effect of intervention. The participants were instructed to walk 30 m under four different conditions: (1) not wearing the robot before the intervention (Pre-condition), (2) wearing the robot without the rhythm assistance (RwoA condition), (3) wearing the robot with rhythm assistance (RwA condition), and (4) not wearing the robot immediately after the intervention (Post-condition). These conditions were conducted in this order over a single day. The third condition was performed three times and the others, once. The arm swing amplitude, stride length, and velocity were increased in the RwA condition compared to the RwoA condition. The coefficient of variance (CV) of the stride duration was decreased in the RwA condition compared to the RwoA condition. These results revealed that the assistance by the robot increased the gait performance of PD patients. In addition, the stride length and velocity were increased and the stride duration CV was decreased in the Post-condition compared to the Pre-condition. These results show that the effect of robot assistance on the patient's gait remained immediately after the intervention. These findings suggest that synchronized rhythmic stimulation on the upper limbs could influence the gait of PD patients and that the robot may assist with gait rehabilitation in these patients.

The Effect of Rhythmic Tactile Stimuli Under the Voluntary Movement on Audio-Tactile Temporal Order Judgement.

The simultaneous perception of multimodal sensory information is important for effective reactions to the external environment. In relation to the effect on time perception, voluntary movement and rhythmic stimuli have already been identified in previous studies to be associated with improved accuracy of temporal order judgments (TOJs). Here, we examined whether the combination of voluntary movement and rhythmic stimuli improves the just noticeable difference (JND) in audio-tactile TOJ Tasks. Four different experimental conditions were studied, involving two types of movements (voluntary movement, involuntary movement) and two types of stimulus presentation (rhythmic, one-time only). In the voluntary movement condition (VM), after the auditory stimulus (cue sound) participants moved their right index finger voluntarily and naturally, while in the involuntary movement condition (IM), their right index finger was moved by the tactile device. The stimuli were provided in a rhythmic or one-time only manner by hitting inside the first joint of the participants' right index finger using a tactile device. Furthermore, in the rhythmical tactile (RT) conditions, tactile stimuli were presented rhythmically to the right index finger 5 times consecutively. On the other hand, in the one-time tactile (1T) conditions, tactile stimuli was presented one-time only to the right index finger. Participants made an order judgment for the fifth tactile stimuli and the first and only auditory stimuli. In our TOJ tasks, auditory-tactile stimulus pairs were presented to participants with varying stimulus-onset asynchronies (SOAs; intervals between the within-pair onsets of the auditory and tactile stimuli). For the two stimuli presented at a time that were shifted by the SOA, the participants were asked to judge which one was presented first, and they were given a two-choice answer. Using a non-parametric test, our results showed that voluntary movement and rhythmic tactile stimuli were both effective in improving the JNDs in TOJ Tasks. However, in the combination of voluntary movement and rhythmic tactile stimuli, we found that there was no significant difference in JNDs in our experiments.