Quantitative evaluation of median nerve motor function in carpal tunnel syndrome using load cell : correlation with clinical, electrodiagnostic, and ultrasonographic findings.

OBJECTIVE: Major complaints of carpal tunnel syndrome (CTS) are sensory components. However, motor deficit also impedes functional status of hand. Contrary to evaluation of sensory function, the objective, quantitative evaluation of median nerve motor function is not easy. The motor function of median was evaluated quantitatively using load cell and its correlation with findings of electrodiagnostic study (EDS) was evaluated. METHODS: Objective motor function of median nerve was evaluated by load cell and personal computer-based measurement system. All of the measurement was done in patients diagnosed as having idiopathic CTS by clinical features and EDS findings. The strength of thumb abduction and index finger flexion was measured in each hand three times, and the average value was used to calculate thumb index ratio (TIR). The correlation of TIR with clinical, EDS, and ultrasonographic findings were evaluated. RESULTS: The TIR was evaluated in 67 patients (119 hands). There were 14 males and 53 females, mean age were 57.6 years (range 28 to 81). The higher preoperative nerve conductive studies grade of the patients, the lower TIR was observed [p<0.001, analysis of variance (ANOVA)]. TIR of cases with thenar atrophy were significantly lower than those without (p<0.001, t-test). TIR were significantly lower in patients with severe median nerve swelling in ultrasonography (p=0.042, ANOVA). CONCLUSION: Measurements of median nerve motor function using load cell is a valuable evaluation tool in CTS. It might be helpful in detecting subclinical motor dysfunction before muscle atrophy develops.

Estimation of sleep onset latency based on the blood pressure regulatory reflex mechanism.

Sleep onset latency (SOL) is an objective indicator of sleepiness and is being used clinically as a diagnostic tool for sleep deprivation. This study proposes a new and less intrusive approach to estimate SOL based on the blood pressure (BP) regulatory reflex mechanism.We hypothesized that the arterial baroreflex, one kind of reflex mechanism for BP regulation, maintains the toning-down effect sleep has on BP. The arterial baroreflex is strongly activated after the time of sleep onset in order to maintain the lowered BP by leading to an increase in heart beat interval (HBI). This observation suggests that the arterial baroreflex has a marked influence on the HBI control with the onset of sleep. As a result, a positive correlation is expected between fluctuations of BP and those of subsequent HBI after sleep onset. To investigate our hypothesis, we determined the relationship between BP and HBI using the R-J and R-R intervals measured from an electrocardiogram and a ballistocardiogram.We estimated SOL using the correlation coefficients corresponding to the relationship between fluctuations of the R-J interval and those of the subsequent R-R interval. The SOLs of ten healthy subjects [age (mean ± SD): 28.72 ± 3.21 years] were estimated using our proposed method and compared with the polysomnography data. The mean absolute error was 0.25 ± 0.35 min, corresponding to a half epoch (15 s) on average. We expect our method will be applicable as a nonintrusive and automatic SOL estimation system that does not require the use of electroencephalogram sensors.

Quantification of cardiac autonomic nervous activities in ambulatory dogs by eliminating cardiac electric activities using cubic smoothing spline.

With the development of an implantable radio transmitter system, direct measurement of cardiac autonomic nervous activities (CANAs) became possible for ambulatory animals for a couple of months. However, measured CANAs include not only CANA but also cardiac electric activity (CEA) that can affect the quantification of CANAs. In this study, we propose a novel CEA removal method using moving standard deviation and cubic smoothing spline. This method consisted of two steps of detecting CEA segments and eliminating CEAs in detected segments. Using implanted devices, we recorded stellate ganglion nerve activity (SGNA), vagal nerve activity (VNA) and superior left ganglionated plexi nerve activity (SLGPNA) directly from four ambulatory dogs. The CEA-removal performance of the proposed method was evaluated and compared with commonly used high-pass filtration (HPF) for various heart rates and CANA amplitudes. Results tested with simulated CEA and simulated true CANA revealed stable and excellent performance of the suggested method compared to the HPF method. The averaged relative error percentages of the proposed method were less than 0.67%, 0.65% and 1.76% for SGNA, VNA and SLGPNA, respectively.

A smart health monitoring chair for nonintrusive measurement of biological signals.

We developed nonintrusive methods for simultaneous electrocardiogram, photoplethysmogram, and ballistocardiogram measurements that do not require direct contact between instruments and bare skin. These methods were applied to the design of a diagnostic chair for unconstrained heart rate and blood pressure monitoring purposes. Our methods were operationalized through capacitively coupled electrodes installed in the chair back that include high-input impedance amplifiers, and conductive textiles installed in the seat for capacitive driven-right-leg circuit configuration that is capable of recording electrocardiogram information through clothing. Photoplethysmograms were measured through clothing using seat mounted sensors with specially designed amplifier circuits that vary in light intensity according to clothing type. Ballistocardiograms were recorded using a film type transducer material, polyvinylidenefluoride (PVDF), which was installed beneath the seat cover. By simultaneously measuring signals, beat-to-beat heart rates could be monitored even when electrocardiograms were not recorded due to movement artifacts. Beat-to-beat blood pressure was also monitored using unconstrained measurements of pulse arrival time and other physiological parameters, and our experimental results indicated that the estimated blood pressure tended to coincide with actual blood pressure measurements. This study demonstrates the feasibility of our method and device for biological signal monitoring through clothing for unconstrained long-term daily health monitoring that does not require user awareness and is not limited by physical activity.

Validation of heart rate extraction through an iPhone accelerometer.

Ubiquitous medical technology may provide advanced utility for evaluating the status of the patient beyond the clinical environment. The iPhone provides the capacity to measure the heart rate, as the iPhone consists of a 3-axis accelerometer that is sufficiently sensitive to perceive tiny body movements caused by heart pumping. In this preliminary study, an iPhone was tested and evaluated as the reliable heart rate extractor to use for medical purpose by comparing with reference electrocardiogram. By comparing the extracted heart rate from acquired acceleration data with the extracted one from ECG reference signal, iPhone functioning as the reliable heart rate extractor has demonstrated sufficient accuracy and consistency.

Capacitive driven-right-leg grounding in Indirect-contact ECG measurement.

For the reduction of common-mode noise level in Indirect-contact ECG (IDC-ECG) measurement, a driven-right-leg grounding method was applied to the IDC-ECG. Because the IDC-ECG does not require any direct contact between the electrodes and the human skin, it is adequate for un-constraining long-term ECG measurement at home and its various applications are now under development. However, larger 60 Hz noise induced by power line appears in IDC-ECG than in conventional ECG, that is a restriction of IDC-ECG application. In this study, the driven-right-leg ground which has been used in conventional direct-contact ECG, was adapted to the IDC-ECG measurement, by feedback of the inversion of amplified common-mode noise to the body through the conductive textile laid on the chair seat. It was shown that the level of 60Hz power line noise was reduced to about -40 dB when the driven-right-leg gain was 1000.

Wakefulness estimation only using ballistocardiogram: nonintrusive method for sleep monitoring.

To evaluate sleep quality or autonomic nervous system, many annoying electrodes have be attached to subjects' body. It can disturb comfortable sleep and, moreover, since it is very expensive experiment, continuous sleep monitoring is difficult. Since heart rate reflects the autonomic nervous system, it is highly synchronized with the sympathetic activation during transition from non-REM sleep to wakefulness. When the transition occurred the heart rate abruptly increased clearly distinguished with other changes. By using this physiology, we tried to classify the wakefulness during the whole night sleep. Our final goal is adopting this method to the continuous monitoring in our daily life. electrocardiogram (ECG) is not the suitable. Subjects have to attach the electrodes by themselves in their housing to obtain ECG. In that point of view, we used the ballistocardiogram (BCG) that is the representative method to obtain heart beat nonintrusively. For ten normal subjects, the wakefulness classifications by using the heart rate dynamics were executed. Nine subjects showed substantial agreement with the visually-scored method, polysomnography (PSG), and only one subject showed moderate agreement in Cohen's kappa value.

Slow-wave sleep estimation on a load-cell-installed bed: a non-constrained method.

Polysomnography (PSG) involves simultaneous and continuous monitoring of relevant normal and abnormal physiological activity during sleep. At present, an electroencephalography-based rule is generally used for classifying sleep stages. However, scoring the PSG record is quite laborious and time consuming. In this paper, movement and cardiac activity were measured unobtrusively by a load-cell-installed bed, and sleep was classified into two stages: slow-wave sleep and non-slow-wave sleep. From the measured cardiac activity, we extracted heartbeat data and calculated heart rate variability parameters: standard deviation of R-R intervals SDNN, low frequency-to-high frequency ratio, alpha of detrended fluctuation analysis and correlation coefficient of R-R interval. The developed system showed a substantial concordance with PSG results when compared using a contingency test. The mean epoch-by-epoch agreement between the proposed method and PSG was 92.5% and Cohen's kappa was 0.62.

REM sleep estimation only using respiratory dynamics.

Polysomnography (PSG) is currently considered the gold standard for assessing sleep quality. However, the numerous sensors that must be attached to the subject can disturb sleep and limit monitoring to within hospitals and sleep clinics. If data could be obtained without such constraints, sleep monitoring would be more convenient and could be extended to ordinary homes. During rapid-eye-movement (REM) sleep, respiration rate and variability are known to be greater than in other sleep stages. Hence, we calculated the average rate and variability of respiration in an epoch (30 s) by applying appropriate smoothing algorithms. Increased and irregular respiratory patterns during REM sleep were extracted using adaptive and linear thresholds. When both parameters simultaneously showed higher values than the thresholds, the epochs were assumed to belong to REM sleep. Thermocouples and piezoelectric-type belts were used to acquire respiratory signals. Thirteen healthy adults and nine obstructive sleep apnea (OSA) patients participated in this study. Kappa statistics showed a substantial agreement (kappa > 0.60) between the standard and respiration-based methods. One-way ANOVA analysis showed no significant difference between the techniques for total REM sleep. This approach can also be applied to the non-intrusive measurement of respiration signals, making it possible to automatically detect REM sleep without disturbing the subject.

Photoplethysmogram measurement without direct skin-to-sensor contact using an adaptive light source intensity control.

We developed a chair-attached, nonintrusive photoplethysmogram (PPG) measuring system for everyday life, unconstrained monitoring using nonskin-contacting sensor-amplifier circuits capable of emitting suitable light intensity adaptable to clothing characteristics. Comparison between proposed and conventional systems showed reasonable correlation and root-mean-squared error levels, indicating its feasibility for unconstrained PPG monitoring.

Noninvasive heart rate variability analysis using loadcell-installed bed during sleep.

Polysomnography is the standard method to score the sleep stages or to determine the quality of sleep. During all night examination, subjects must attach complicate and numerous electrodes on their body to acquire the biosignals. They can influence participants' sleep stage transition or sleep pattern, and the method seems intricate. In many researches, it is reported that autonomic nervous system (ANS) is varying with sleep stage transition and heart rate variability (HRV) is one of the indices which reflects the changes of autonomic nervous system. In this point of view, we can estimate the sleep quality by observing the HRV variation. In this study, to analyze the heart rate variability, we introduce a new system that can detect the heart beats of subjects during sleep by using bed installed load-cell sensors. The pressure to the sensor changes with the pulsation of the heart and we consider it as ballistocardiogram, the physical heart beat signal. To validate our system, we adopted this system for the 4 subjects with the polysomnography. The results show the LF/HF ratio of the heart rate, one of the reflection parameters of ANS, acquired from the system for each sleep stage. To validate the results, the HRV from electrocardiogram using Ag-AgCl electrodes will be compared.