Masaru Yokoe

Opening velocity, a novel parameter, for finger tapping test in patients with Parkinson's disease

OBJECTIVES A new system consisting of an accelerometer and touch sensor was developed to find objective parameters for the finger tapping (FT) test in patients with Parkinsons disease (PD). METHODS We recruited sixteen patients with PD and thirty-two age-matched healthy volunteers (HVs). By using this new system, various parameters related to velocity, amplitude, rhythm and number in the FT test were measured in patients with PD and examined in comparison with those of HVs on the basis of the Unified Parkinsons Disease Rating Scale (UPDRS) FT score. RESULTS The new system allowed us to measure fourteen parameters of FT movement very easily, and a radar chart showed obvious differences in most of these parameters between HVs and patients with PD. Principal component analysis showed that fourteen parameters were classified into three components: (1) both mean and standard deviation (SD) of both amplitude and velocity, (2) number of FT for 60s and mean FT interval, and (3) SD of FT interval. The first (velocity- and amplitude-related parameters) and third (rhythm-related parameters) components contributed to discrimination of PD from HVs. Maximum opening velocity (MoV) was the best of these parameters because of its sensitivity and association with the UPDRS FT score. CONCLUSIONS A novel system for the FT test, which is compact, simple and efficient, has been developed. Velocity- and amplitude-related parameters were indicated to be valuable for evaluation of the FT test in patients with PD. In particular, we first propose that MoV is a novel marker for the FT test.

Quantitative magnetic detection of finger movements in patients with Parkinson’s disease

To develop a new measurement tool for quantitatively detecting the finger movement of a patient with Parkinsons disease (PD), we designed a magnetic sensing system consisting of a magnetic induction coil, a sensing coil, and a circuit unit. The sensing coil detects the inducted magnetic field that varies with the distance between the two coils, and the detected signals are demodulated in the circuit unit in order to obtain the variation voltage from the oscillation frequency. To obtain a coefficient for converting voltage to distance, we measured the output voltages for seven fixed finger positions of 12 normal volunteers. The voltage differences corresponding to the finger movement in 20 PD patients, six age-matched controls, and 12 normal volunteers were then recorded for 30s. To investigate the velocity and acceleration of the finger movement, we calculated their waveforms from the measured displacement waveform. We also detected the main frequency of the tapping rhythm by using a fast Fourier transform (FFT). The averaged amplitude of each waveform decreased with the disorder in the Hoehn-Yahr (HY) stage, while the averaged tapping frequency of PD patients did not have any correlation with this stage. It can be concluded that this magnetic sensing system can assess finger movement quantitatively.

A novel method for systematic analysis of rigidity in Parkinson's disease†

We propose a novel system that analyzes the components of rigidity in Parkinsons disease (PD) usually perceived by physicians, in a very simple and systematic way for routine clinical practice. Our system is composed of two compact force sensors, a gyroscope, and EMG surface electrodes. Muscle tone was assessed in 24 healthy elderly subjects and 27 PD patients by passive extension and flexion of the elbow joint with ramp‐and‐hold trajectory. Torque and angle data in the dynamic phase were used to calculate “elastic coefficients” in extension and flexion, and the mean value of torque in each dynamic phase at each joint angle (defined as “Bias”) was also calculated. The muscle activity index in the static phase (EMG Index) was obtained for both biceps brachii (BB) and triceps brachii (TB) muscles. “Elastic coefficients,” sum of the “difference of Bias” and “EMG Index” for BB all correlated well with UPDRS score. Based on our results, Parkinsonian rigidity consists of both an “elastic” component and a “difference of Bias” component, and neurologists may assess greater rigidity when either one or both components are high in value. The EMG index was useful for differentiating PD patients with slight rigidity from healthy elderly adults.

Measurement and evaluation of finger tapping movements using magnetic sensors

This paper proposes a quantitative measurement and evaluation method of finger tapping movements for diagnosis support and assessment of motor function. In this method, a magnetic sensor consisting of two coils is used to measure movement. The coil voltage induced by the electromagnetic induction law changes depending on the distance between the two coils; this enables estimation of the distance between two coil-bearing fingertips from the voltage measured by the nonlinear modeling relationships between the voltages and distances. Further, the finger movements measured are evaluated by computing ten indices such as the finger tapping interval, and radar charts of the evaluation indices and phase-plane trajectories of the finger movements are then displayed in real time on a monitor. Evaluation experiments were performed on finger movement in 16 Parkinsons disease patients and 32 normal elderly subjects, with the results showing that all evaluation indices differ significantly for each subject (p < 0.05).

Measurement and Evaluation of Finger Tapping Movements Using Log-linearized Gaussian Mixture Networks

This paper proposes a method to quantitatively measure and evaluate finger tapping movements for the assessment of motor function using log-linearized Gaussian mixture networks (LLGMNs). First, finger tapping movements are measured using magnetic sensors, and eleven indices are computed for evaluation. After standardizing these indices based on those of normal subjects, they are input to LLGMNs to assess motor function. Then, motor ability is probabilistically discriminated to determine whether it is normal or not using a classifier combined with the output of multiple LLGMNs based on bagging and entropy. This paper reports on evaluation and discrimination experiments performed on finger tapping movements in 33 Parkinson’s disease (PD) patients and 32 normal elderly subjects. The results showed that the patients could be classified correctly in terms of their impairment status with a high degree of accuracy (average rate: 93.1 ± 3.69%) using 12 LLGMNs, which was about 5% higher than the results obtained using a single LLGMN.

Finger Taps Movement Acceleration Measurement System for Quantitative Diagnosis of Parkinson's disease

The purpose of this study was to develop a finger taps acceleration measurement system for the quantitative diagnosis of Parkinsons disease. The system was composed of two 3-axis piezoelectric element accelerometers, a pair of touch sensors made of thin stainless steel sheets, an analog-digital(AD) converter and a personal computer (PC). Fingerstalls,with these sensors, were attached to subjects index finger and thumb. The acceleration and output of the touch sensors were recorded using the PC during the finger taps movements. Intervals between the single finger taps movements were calculated from the measured output of the touch sensors. Velocities during the single finger taps movements were calculated by integrating the measured acceleration. The amplitudes were calculated by integrating the velocities. The standard deviation of the single finger taps intervals, average of maximum single finger taps velocities and average of maximum single finger taps amplitudes were calculated from them. They were used as features for the quantitative diagnosis of Parkinsons disease. The developed system was used to conduct finger taps tests employing 27 normal subjects and 16 Parkinsons diseases subjects. The subjects were asked to execute continuous finger taps movement for 60 s. It was shown that the acceleration and output of the touch sensors could be measured and the features could be extracted.

Measurement system of finger-tapping contact force for quantitative diagnosis of Parkinson's disease

The purpose of this study was to develop a measuring system of contact force in finger-tapping of Parkinsons disease patients and to show its effectiveness for quantitative diagnosis. This system was composed of a pair of 3-axis accelerometers, a touch sensor an analog to digital converter and a personal computer (PC). Firstly, a transfer function representing relation between the contact force and the accelerometer output during the finger contact phase of finger-tapping was determined. This means that the finger-tapping contact force could be estimated from the measured acceleration by using the determined transfer function. Secondly the developed system was applied to 27 normal subjects and 16 Parkinsons diseases subjects. Score of UPDRS finger tap test was evaluated for each subject by a neurologist. Finally, these sensors were attached to subjects index finger and thumb, and sensor signals were recorded and processed within the PC. The subjects were asked to execute continuous finger taps movement for 60 s. It was shown that the contact force was smaller as the subject was with the larger UPDRS score of tap test.

Analysis of spatial temporal plantar pressure pattern during gait in Parkinson's disease

Spatial temporal plantar pressure patterns measured with sheet-shaped pressure sensor were investigated to extract features of gait in Parkinsons disease. Both six subjects of Parkinsons disease (PD) and elderly fourteen normal control subjects were asked to execute usual walking on the pressure sensor sheets. Candidate features were step length, step time, gait velocity and transition of center of pressure to foot axis direction. The step length and gait velocity were smaller in PD subjects than those in normal subjects. Time of step cycle in three PD subjects were longer than that in normal subjects while the times of other PD subjects were similar to those of control subjects. The length from heel contact to toe off within one footprint was small in the subjects with short step length. Such possibility was indicated that Parkinsons disease in gait could be separated from normal subjects by these features.

The “Cross” Signs in Patients With Multiple System Atrophy: A Quantitative Study

Patients with multiple system atrophy (MSA) may show the “cross” sign in the pontine base that has been considered as an expression of the degeneration of pontine neurons and transverse pontocerebellar fibers. However, correlations between pontine base atrophy and existence of “cross” sign have not been fully investigated. The authors studied 68 patients with MSA (47 MSA‐C [predominantly cerebellar ataxia], 21 MSA‐P [predominantly parkinsonism], mean [±SD ] 58.7 ± 10.9 years). T1‐weighted (T1W) sagittal and axial images and T2‐weighted (T2W) axial images were obtained for all patients and controls. To measure the areas of pontine basis and cerebellar vermis, the authors used midsagittal T1W images and analyzed a bit map transformed on a computer. They classified atrophy in the pontine base into 3 grades. There is significant correlation between atrophies of pontine base and existence of the cross sign. All patients with a smaller area of pontine base 2 standard deviations below those of normal controls had the cross sign. This supports that existence of the cross sign depends only on the extent of pontine base atrophies.

Estimation of human finger tapping forces based on a fingerpad-stiffness model

This paper proposes a method of estimating fingertip forces in finger tapping movements based on human fingerpad characteristics. Since the human fingerpad exhibits elasticity, the proposed technique recreates the relationship between the fingertip force and the displacement generated between the thumb and index fingerpads as a fingerpad-stiffness model. Then, using this model, the force between the two fingertips (the fingertip force) can be estimated from the measured fingerpad deformation only. As the method does not require any sensors to be attached to the finger contact surface to measure fingertip force, it can be used to evaluate the tendency of force in natural and unconstrained finger tapping movements conducted by the subject. In the experiments conducted, fingertip forces and the displacement of the two fingerpads generated when the subjects pinched and pushed a force sensor with the thumb and index finger were measured to approximate the relationships between fingerpad force and deformation. The results indicated that human fingerpad characteristics can be expressed using a fingerpad-stiffness function (including an exponential function), and that fingerpad forces can be estimated using the proposed model. Furthermore, comparison between a Parkinsons disease (PD) patient and a healthy subject confirmed differences in the finger tapping forces for each. This implies the possibility of assessing motor function in PD patients using the finger tapping force evaluation method proposed in this paper.