Toshitaka Yamakawa

Cooling of the epileptic focus suppresses seizures with minimal influence on neurologic functions.

Purpose:  Focal brain cooling is effective for suppression of epileptic seizures, but it is unclear if seizures can be suppressed without a substantial influence on normal neurologic function. To address the issue, a thermoelectrically driven cooling system was developed and applied in free‐moving rat models of focal seizure and epilepsy.

Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability Features

Objective: The present study proposes a new epileptic seizure prediction method through integrating heart rate variability (HRV) analysis and an anomaly monitoring technique. Methods: Because excessive neuronal activities in the preictal period of epilepsy affect the autonomic nervous systems and autonomic nervous function affects HRV, it is assumed that a seizure can be predicted through monitoring HRV. In the proposed method, eight HRV features are monitored for predicting seizures by using multivariate statistical process control, which is a well-known anomaly monitoring method. Results: We applied the proposed method to the clinical data collected from 14 patients. In the collected data, 8 patients had a total of 11 awakening preictal episodes and the total length of interictal episodes was about 57 h. The application results of the proposed method demonstrated that seizures in ten out of eleven awakening preictal episodes could be predicted prior to the seizure onset, that is, its sensitivity was 91%, and its false positive rate was about 0.7 times per hour. Conclusion: This study proposed a new HRV-based epileptic seizure prediction method, and the possibility of realizing an HRV-based epileptic seizure prediction system was shown. Significance: The proposed method can be used in daily life, because the heart rate can be measured easily by using a wearable sensor.

A circuit design of a smart RF ID tag for heartbeat signal extraction

A mixed-signal CMOS circuit design of a smart RF ID tag for heartbeat signal extraction is proposed. This smart RF ID tag has been under development for monitoring heartbeat signals from an electrocardiogram (ECG) microsensor and/or a pressure microsensor implanted in a transgenic animal. This tag is remotely powered by RF electromagnetic induction. The signal packet consisting of an identification code of 64 bits in length and a spike-pulse sequence of heartbeat signals are transmitted to a reader system using BASK modulation.

Neuroprotective effects of focal brain cooling on photochemically-induced cerebral infarction in rats: Analysis from a neurophysiological perspective

Although systemic hypothermia provides favorable outcomes in stroke patients, it has only been adopted in a limited number of patients because of fatal complications. To resolve these issues, focal brain cooling (FBC) has recently drawn attention as a less-invasive treatment for brain injuries. Therefore, we investigated whether FBC has a favorable effect on focal cerebral ischemia (FCI). Male-adult-Wistar rats were used. Under general anesthesia, a small burr hole was made and FCI was induced in the primary sensorimotor area (SI-MI) using photothrombosis. An additional craniotomy was made over the SI-MI and FBC was performed at a temperature of 15°C for 5h. Electrocorticograms (ECoG) were recorded on the border cortex of the ischemic focus. Thereafter, rats were sacrificed and the infarct area was measured. In another experiment, rats were allowed to recover for 5 days after cooling and neurobehavioral function was evaluated. FBC suppressed all ECoG frequency bands during and after cooling (p<0.05), except for the delta frequency band in the precooling versus rewarming periods. The injured areas in the cooling and non-cooling groups were 0.99±0.30 and 1.71±0.54 mm(2), respectively (p<0.03). The grip strength at 2 days after surgery was preserved in the cooling group (p<0.05). We report the novel finding that epileptiform discharges were suppressed in the ischemic border, the infarct area was reduced and neurobehaviour was preserved by FBC. These results indicate that FBC is neuroprotective in the ischemic brain and has demonstrated therapeutic potential for cerebral infarction.

Real-time heart rate variability monitoring employing a wearable telemeter and a smartphone

A telemetry system for the measurement of heart rate variability (HRV) has been developed with a low-cost manufacturing process and a low-power consumption design. All the components and functions for the RRI measurement were implemented on a wearable telemeter which can operate for up to 10 hours with a rechargeable Li-Polymer battery, and the RRI data is stored into a smartphone via a Bluetooth wireless transmission. In a long-term measurement of a young subject that extended over 48 hours in total, the results showed a 1% probability of recurring errors. The obtained results suggest that the proposed fully-wearable system enables the continuous monitoring of HRV for both clinical care and healthcare operated by a non-expert.

Development of an Implantable Flexible Probe for Simultaneous Near-Infrared Spectroscopy and Electrocorticography

A combination of near-infrared spectroscopy (NIRS) and electrocorticography (ECoG) provides beneficial information on cortical activity from different aspects. Integration of such multimodal measurement capability into a single apparatus and the direct measurement of cortical activity during chronic subdural implantation may be a powerful means for clinical diagnosis and neuroscience. However, an optical fiber-based NIRS probe cannot be miniaturized for implantation into the brain, and the light-scattering effect of ECoG electrodes in NIRS measurements is unknown. We describe here the development of a flexible probe, small enough for chronic subdural implantation, for simultaneous NIRS and ECoG. Two light-emitting diodes of different wavelengths and two photodiodes were mounted on a polyimide-based flexible substrate, and ECoG electrodes were formed with a design minimizing artifacts in NIRS recording. The fabricated probe measured ECoGs at sufficient spatial resolution and submicromolar changes in hemoglobin concentrations in in vivo experiments with acute implantation into a rat. Comparison of measured changes in hemoglobin concentrations for different source-detector distances reveals the reliability of the measured values and the practicality of the simulation model. The proposed intracranial multimodality probe may provide beneficial evidence for pre- and intrasurgical assessment of neurosurgery and reveal the interaction of electrophysiology and hemodynamics at high spatial resolution without artifacts due to scalp blood flow.

Design and Experiments of a Novel Low-Ripple Cockcroft-Walton AC-to-DC Converter for a Coil-Coupled Passive RFID Tag

A low-ripple diode charge-pump type AC-DC converter based on the Cockcroft-Walton diode multiplier is proposed for coil-coupled passive IC tags in this paper. This circuit is developed as a power supply for passive RFID tags with smart functions such as heart rate detection and/or body temperature measurement. The proposed circuit converts wirelessly induced power to a low-ripple DC voltage suitable for a 13.56 MHz RFID tag. The proposed circuit topology and the principle of operation are explained and treated theoretically by using quasi-equivalent small-signal models. The proposed circuit was implemented on a PCB. And it was confirmed that the proposed circuit provides 3.3 V DC with a ripple of less than 20 mV when a 4Vp-p sinusoidal input is applied. Under this condition, the maximum output power is about 310 μW. The measured results were in good agreement with theoretical and HSPICE simulation results.

Design of a CMOS Heartbeat Spike-Pulse Detection Circuit Integrable in an RFID Tag for Heart Rate Signal Sensing

A circuit design of a CMOS integrable heartbeat spike-pulse detection circuit is proposed in this paper. This circuit is developed to be implemented on a small-sized RFID sensor tag (which we call a smart RFID tag throughout this paper) implanted in a transgenic mouse. This circuit can detect only spike pulses with magnitude higher than the prescribed level from a mouses heartbeat signal, which is sensed by a small microphone sensor and/or an electrocardiogram (ECG) microsensor attached to the RFID tag. The proposed circuit features robustness to the device tolerances and temperature variations thanks to its auto-bias technique based on good device matching and its switched-capacitor auto offset-canceling technique. The circuit was fabricated by a standard 0.35 μm CMOS process and works at a supply voltage of 3 V and dissipates less than 800μW.

A circuit design of ID-code and heartbeat signal processing blocks of a smart RF ID tag for mice

The design of a mixed-signal CMOS circuit of ID-code and heartbeat signal processing blocks of a smart RF ID tag for mouses heartbeat signal extraction is proposed. This smart RF ID tag has been under development for monitoring heartbeat signals from an electrocardiogram (ECG) microsensor and/or a pressure microsensor implanted in a transgenic mouse. This tag has an ID-code of 64-bits in length and generates heartbeat signal in the form of a position-pulse sequence

Heart rate variability features for epilepsy seizure prediction

Although refractory epileptic patients suffer from uncontrolled seizures, their quality of life (QoL) may be improved if an epileptic seizure can be predicted in advance. In the preictal period, an excessive neuronal activity of epilepsy affects the autonomic nerve system. Since the fluctuation of the R-R interval (RRI) of an electrocardiogram (ECG), called heart rate variability (HRV), reflects the autonomic nervous function, an epileptic seizure may be predicted through monitoring HRV data of an epileptic patient. In the present work, preictal and interictal HRV data of epileptic patients were analyzed for developing an epilepsy seizure prediction system. The HRV data of five patients were collected, and their HRV features were calculated. The analysis results showed that frequency HRV features, such as LF and LF/HF, changed at least one minute before seizure onset in all seizure episodes. The possibility of realizing a HRV-based seizure prediction system was shown through these analysis.