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Journal of Medical and Biological Engineering, 33(1): 79-86 79

Uninterrupted Wireless Long-Term Recording of Sleep

Patterns and Autonomic Function in Freely Moving Rats

I-Te Hsieh1,2,3 Cheryl Ching-Hsiu Yang2,3,4 Chun-Yu Chen2,3 Guo-She Lee2,3,4,5

Fu-Jen Kao1 Kuan-Liang Kuo6 Terry Bo-Jau Kuo2,3,4,*

1Institute of Biophotonics, National Yang-Ming University, Taipei 112, Taiwan, ROC 2Institute of Brain Science, National Yang-Ming University, Taipei 112, Taiwan, ROC

3Sleep Research Center, National Yang-Ming University, Taipei 112, Taiwan, ROC 4Department of Education and Research, Taipei City Hospital, Taipei 103, Taiwan, ROC

5Department of Otorhinolaryngology, Ren-Ai Branch, Taipei City Hospital, Taipei 103, Taiwan, ROC 6Department of Family Medicine, Ren-Ai Branch, Taipei City Hospital, Taipei 103, Taiwan, ROC

Received 6 Oct 2011; Accepted 3 Feb 2012; doi: 10.5405/jmbe.1039

Abstract

When studying long-period oscillations and subtle physiological variations, including sleep/wake transitions,

autonomic functions, and physical activities, a technique that provides uninterrupted recordings of the various

physiological signals for more than one day with the lowest possible artificial disturbances and with a minimum

number of physiological effects is necessary. This study integrates a wireless recharging circuit into a miniature

physiological wireless sensor to develop an uninterrupted wireless recording system for parietal electroencephalograms,

occipital electroencephalograms, nuchal electromyograms, electrocardiograms, and 3-axis acceleration signals. The

wireless recharging circuit captures power from an alternating magnetic field. Control and sham rats underwent

traditional head-mount surgery but only the sham rats were implanted with a non-functional advanced wireless sensor

in their abdomen. Functional advanced wireless sensor units were intra-abdominally implanted into the experimental

rats. All physiological signals were recorded without interruption for over ten days. There was no difference in the

sleep/wake patterns, physical activity, body weight, and autonomic functioning, which was assessed by heart rate

variability (HRV), among the control, sham, and experimental rats. Furthermore, the continuous recording revealed the

circadian rhythms in the HRV variables, namely a 24-hour cycle in R-R intervals (RR) and the total power, high-

frequency power, and low-frequency power of the RR spectrum. It is confirmed that the proposed system creates

minimal disturbances to the rat’s physiology and is capable of ultra-long-term recording of daily, weekly, monthly, or

even lifelong rhythms on the animals’ sleep/wake structure and autonomic functioning.

Keywords: Uninterrupted recording, Wireless recharge, Long-period rhythm, Sleep/wake pattern, Heart rate variability

(HRV)

1. Introduction

Behavior is an integration of various physiological

functions and therefore deciphering these physiological

functions is a fundamental part of behavioral science. Recording

physiological signals is of particular importance to our

understanding of the behavioral aspects of laboratory animals,

from which subjective measures are unavailable. Numerous

studies have recorded bioelectric signals from laboratory

animals via tethered systems. In such studies, the animals are

directly connected to a recording amplifier, and thus their

* Corresponding author: Terry Bo-Jau Kuo

Tel: +886-2-28267058; Fax: +886-2-28273123

E-mail: [email protected]

locomotor activity is restricted and they are under additional

stress from the messy cable [1]. A number of researchers have

thus developed wireless recording systems that allow

physiological signals to be collected under conditions that best

represent the normal state of the animal [2].

Wireless recording systems combine a miniature sensor/

transmitter unit and a remote receiver unit. The miniature sensor

detects the biological signals in the animal, and the transmitter

broadcasts the measurement data to the remote receiver. The

receiver then digitizes the analog signal, with the resulting data

stored on a data acquisition system. The sensor/ transmitter can

be non-implantable, such a jacket telemetry system or a

headstage, or implantable, such as a subcutaneous or

intra-abdominal system. Although wireless recording systems

are superior to conventional cable systems in terms of motion

J. Med. Biol. Eng., Vol. 33 No. 1 2013 80

artifacts and power line interference with animals, their power

supply is a challenge. Current wireless telemetry devices are

usually battery operated. For non-implanted units, flat batteries

can be replaced with full-size ones. Many commercially

available wireless implants are not suitable for long-term

implantation because of the need for battery replacement, even

though some improvement with respect to battery energy

density has been achieved [3]. To solve the battery problem,

inductive power supply systems that do not need a battery have

been developed, but the small amount of power available has

limited their applicability when high-bandwidth signals or

multi-channel recording is used [3,4]. The present study thus

adopts inductive power transfer technology for recharging

implant batteries.

The inductively coupled system used in this study, there are

coils under the home cage of the animal implanted with the

measurement device; these coils generate a magnetic field. The

implanted device contains a rechargeable battery and a pickup

coil. Power is wirelessly delivered to the battery when the

magnetic field is aligned with the pickup coil. This technology

has been used for powering implantable devices for recording of

a wide variety of physiological signals, including

electroencephalograms (EEGs), electrocardiograms (ECGs),

electromyograms (EMGs), and blood pressure. For small

laboratory animals, the most success has been demonstrated

when recording ECG signals. It has been shown that ECG

signals can be sampled and recorded at 2,000 Hz in conscious

rats for up to 4 months. Lifetime monitoring has also been

suggested. Based on the successful recording of high-band-

width signals, the technology is expected to work when

simultaneously collecting a variety of different physiological

signals.

In the field of sleep research, EEG and EMG signals are

used to differentiate between sleep and wake stages. The

inclusion of other biological signals is helpful if other

physiological functions are to be investigated. It has been

reported that weekly, seasonal, or even annual variations can be

observed in mammalian sleep [5-7]. However, the recording

time of currently available polysomnographic recording systems

is prohibitively short for investigating rhythms of such length. In

addition, although it has been shown that ECG signals can be

stably collected by implantable telemeters from conscious

animals, other functional aspects, such as heart rate variability

(HRV) analysis for autonomic assessment, have not yet been

studied in this way. Therefore, the present study develops a fully

implantable conductively powered device that is capable of

continuously gathering a wide range of physiological signals

(EEG, EMG, ECG, and physical activity). The performance of

the device was verified by studying the health on conscious rats

in terms of sleep wake patterns and autonomic functioning. The

long-term data are analyzed. The effect of the long-term

uninterrupted recording of electrophysiological signals of freely

moving rats on their sleep/wake patterns and autonomic

functioning is also investigated.

2. Materials and methods

A two-phase study was conducted to confirm the

feasibility and biological effects of the wireless system. The

wireless recording system developed for this purpose comprises

a computer, a miniature physiological wireless sensor (WS-I;

K&Y Lab, Taipei, Taiwan, size: 20 × 17.5 × 10 mm3, weight: 5

g), a wireless recharging circuit, and a wireless recharging table

(size: 55 × 26 cm2). To determine the biological effects, the

body weights, sleep/wake patterns, and cardiac autonomic

functions of control, sham, and experimental rats were

compared after recovery from implantation.

2.1 System construction

2.1.1 Hardware design

In order to collect parietal EEG (EEG-p), occipital EEG

(EEG-o), nuchal EMG, ECG, and 3-axis acceleration signals

uninterruptedly from freely moving rats, a WS-I that contains

various units, namely an analog amplifier, a microcontroller

unit (MCU), a radio-frequency (RF) transceiver, and a

lithium-ion polymer battery. The WS-I and a wireless

recharging circuit were integrated as an advanced sensor

(WS-II; size: 42 × 20 × 10 mm3, weight: 8.3 g). A block

diagram of WS-II is shown in Fig. 1(a). The EEG-p, EEG-o,

EMG, ECG, and 3-axis acceleration signals are amplified

1000-fold, 1000-fold, 1000-fold, 538-fold, and 1-fold,

respectively, and filtered between 0.16-48, 0.16-48, 34-103,

0.72-106, 0-31.8 Hz, respectively. These signals are then

relayed to the MCU, which samples them at 500, 250, 125, and

62.5 Hz, respectively. After being sampled, the signals are

synchronously digitalized by a 12-bit analog-to-digital

converter and relayed to the RF transceiver. The RF

transceiver, which operates at 2.4 GHz, receives the commands

and transmits the data to a computer via an RF dongle

wirelessly. The lithium-ion polymer battery has a capacity of

80 mAh and is rechargeable; it is used as a power supply for

the unit. The battery voltage is considered 100% charged at 4.2

V. It has a nominal voltage of 3.7 V and a cut-off voltage of

2.5 V.

2.1.2 Wireless recharging technique

Faraday’s law of induction states that the induced

electromotive force in any closed circuit is equal to the time

rate of change of the magnetic flux through the circuit. The

wireless recharging technique is designed based on Faraday’s

law. The hardware contains a primary side that generates an

alternating magnetic field and a secondary side that consists of

a closed circuit that is involved in capturing the alternating

magnetic field from the primary side wirelessly. A wireless

recharging table (the primary side) that generates a 125-kHz

alternating current in a loop was designed. A wireless

recharging circuit (the secondary side) that generates electrical

energy by capturing the alternating magnetic field wirelessly

was also designed. The wireless recharging circuit contains an

inductive coil and a voltage modulation module. The inductive

coil (size: 20 × 17.5 × 5.0 mm3) wirelessly captures the

alternating magnetic field generated by the primary side. A

flow chart is shown in Fig. 1(b). The voltage modulation

module was designed to carry out rectification, voltage

regulation, filtering, voltage modulation, and charging

Wireless Recording of Sleep Patterns and Electrocardiography in Rats 81

(a) (b)

(c) (d)

Figure 1. (a) Uninterrupted wireless recording system. Up to seven biological signals, including parietal electroencephalogram (EEG-p), occipital

electroencephalogram (EEG-o), nuchal electromyogram (EMG), electrocardiogram (ECG), and 3-axis acceleration, are captured by the

wireless sensor through a digital circuit and then relayed by an analog-to-digital converter to a microcontroller. The signals are digitalized by

the microcontroller, and wirelessly transmitted at a radio frequency of 2.4 GHz to a RF dongle and stored in a computer for off-line analysis.

(b) Wireless recharging technique block diagram. The wireless recharging table (primary side) generates a 125-kHz alternating magnetic

field. The wireless recharging circuit (secondary side) uses an inductive coil. Power uptake takes place via rectification, a voltage regulator,

a filter, voltage modulation, and charging functions. (c) Schematic illustration of the main components of the system. A computer with an

RF dongle, a wireless sensor (WS-II), and the wireless recharging table are the main components of system. The wireless recharging table

recharges WS-II, which senses the rat’s EEG, EMG, and ECG signals. WS-II then transmits this information to the computer. The maximum

transmission distance is 10 meters. (d) Schematic representation of the intra-abdominal sensor implantation. The sensor is fixed

intra-abdominally to the abdominal muscles, and the electrodes that measure EEG-p, EEG-o, EMG, and ECG are placed subcutaneously.

functions. A constant-voltage charging mode is used. The

charging voltage is limited to 4.2 V to protect the lithium-ion

polymer battery. All circuits were integrated into WS-II and

packaged in biphenol epoxy and silica gel to create a water-

proof unit. The main components are shown in Fig. 1(c). The

computer with an RF dongle receives the data transmitted by

WS-II. All signals are collected by WS-II, which is recharged

wirelessly by the recharging table.

2.2 Animal experiment

2.2.1 Animals

Experiments were carried out on 15 adult male Wistar-

Kyoto (WKY) rats (250-350 g in weight, 12 weeks old), which

were randomly divided into three groups (control, sham, and

experimental) with equal numbers of rats in each group. After

surgery, the rats were given an antibiotic (chlortetracycline,

topical) and housed individually in standard translucent acrylic

cages for ten days for recovery and habitation. The same type

of cage was also used during data recording. The rats were kept

in a sound-attenuated room with a 12:12 hour light-dark cycle

(08:00 AM to 08:00 PM lights on) and at an appropriate

temperature (20 2 °C) and humidity (40-70%). The cage was

cleaned and replenished with food and water every four days.

The rats were obtained from the National Laboratory Animal

Center in Taiwan based on the principles listed in the Position

of the American Heart Association on Research Animal Use.

The experimental protocols were approved by the Institutional

Animal Care and Use Committee of National Yang-Ming

University.

2.2.2 Animal preparation and experimental protocol

All rats underwent the surgery at the age of 12 weeks.

After ten days of recovery, behavioral tests were performed,

and their body weights were recorded. The skull surface was

exposed with two recording screws fixed into it for the parietal

EEG (2.0 mm posterior to and 2.0 mm lateral to the bregma)

and the occipital EEG (2.0 mm anterior to and 2.0 mm lateral

to the lambda), both referenced to a ground screw in the

occipital bone (2 mm caudal to the lambda), under anesthesia

with pentobarbital (50 mg/kg, ip). ECG signals were recorded

by a pair of microwires placed subcutaneously (one was

between the cervical and thoracic levels, the other at the lumbar

level). EMG signals were recorded via two 7-stranded stainless

steel microwires bilaterally inserted into the dorsal neck

muscles. In the control group, all the signals were relayed to a

common connector that was fixed onto the head [8] by wires

and WS-I, which was connected to the common connector

transmitted data to a computer wirelessly. The sham group

members were implanted with a non-functional WS-II in the

abdomen. In the experimental group, a functional WS-I was

implanted in the abdomen (Fig. 1(d)), and was recharged with

the wireless recharging table. All signals were relayed to their


amplifiers by wires. The WS-II transmitted the data to the

computer wirelessly. The detailed surgical procedure for the

implantation of the electrodes can be found elsewhere [9-12].

All groups were recorded for ten days starting after a ten-day

recovering period. Only the experimental group was recorded

above the wireless recharging table.

2.3 Data analysis

2.3.1 Sleep/wake patterns and physical activity

The sleep/wake analysis was performed according to a

semi-automatic computation procedure that has been

previously described in detail [9,11,12]. The consciousness

states of the animals were discriminated into active waking

(AW), quiet sleep (QS), and paradoxical sleep (PS) according

to the EEG and EMG signals. Continuous power spectral

analysis was applied to the EEG and EMG signals, from which

the mean power frequency of the EEG (MPF) and the power

magnitude of the EMG were quantified. The duration of the

time segments was 16 s; successive time segments had a 50%

overlap (time resolution: 8 s). For each 8-s time segment, the

sleep-wake stage was defined as AW if the corresponding MPF

was greater than a pre-defined MPF threshold (TMPF) and the

EMG power was greater than a pre-defined EMG power

threshold (TEMG); it was defined as QS if the corresponding

MPF was less than the TMPF and the EMG power was less than

the TEMG; it was defined as PS if the corresponding MPF was

greater than the TMPF and the EMG power was less than the

TEMG. If the MPF was less than TMPF and the EMG power was

greater than TEMG, the stage could not be determined and the

corresponding cardiovascular signals were not analyzed.

To define the threshold, the recording data were cut into

6-h periods. A histogram analysis was then conducted on the

6-h time series of MPF, from which two separate populations

respectively related to the AW/PS complex and QS were

identified. TMPF was set to discriminate these two populations.

The histogram of the EMG time series also had two

populations, which were respectively related to AW and the

QS/PS complex. TEMG was set to discriminate these two

populations. TMPF and TEMG can be manually fine-tuned by an

experienced rater. Finally, a mature stage was defined as any

sleep stage that persisted unchanged for at least 6 epochs

(around 56 s). Any sleep-wake stage persisting for less than 6

epochs was regarded as a transient interruption. QS is also

known as slow-wave sleep, whereas PS is equivalent to rapid-

eye-movement sleep [13]. The time, number, and duration of

the three stages were calculated and used as indicators of the

sleep/wake patterns. The sum of the difference in each axis

acceleration signal from the 3-axis accelerometer was

calculated and used to measure the rat’s physical activity under

the various sleep/wake states (AW, QS, and PS).

2.3.2 Heart rate variability parameters

HRV is a cardiac phenomenon by calculated the variation

of heart rate in the beat-to-beat interval (R-R intervals), where

R is a point corresponding to the peak of the QRS complex of

the ECG wave; RR is the interval between successive Rs. The

detailed analytical procedures used for HRV have been

previously described [11,12,14]. Preprocessing of the ECG

signals was designed according the recommended procedures

for HRV analysis [15]. The R-R interval time series were

sampled at intrinsically irregular intervals. The Fourier

transform was applied to the time series with uniform intervals

between samples. Thus, the R-R interval time series was

resampled and linearly interpolated at 64 Hz to provide

continuity in the time domain. A Hamming window was

applied to each 8-s epoch to attenuate the leakage effect of the

power spectrograms. An algorithm was then used to estimate

the power spectral density using the fast Fourier transform [16].

For each 16-s period, the high-frequency (HF) (0.6-2.4 Hz) and

low-frequency (LF) (0.06-0.6 Hz) power of the RR

spectrogram were quantified using integration, that is, by

calculating the area of the power spectral density between the

specified frequencies, expressed in units of milliseconds

squared [15]. The mean of each HRV parameter under the

various sleep/wake states (AW, QS, and PS) and light-dark

periods and the LF to HF ratio (LF/HF) were also calculated.

Previous studies have indicated that HF is an indicator of

cardiac parasympathetic activity [17], and the ratio LF/HF is

considered by some investigators to mirror sympathovagal

balance or to reflect sympathetic modulations [15,18].

2.4 Statistical analysis

All data are represented as mean ± standard error of the

mean (mean ± SEM). Repeated measures one-way analysis of

variance (ANOVA) was used to examine the differences

between the rats’ performance across the three groups for the

various sleep patterns and autonomic functions. p < 0.05 was

considered statistically significant.

3. Results and discussion

3.1 Functional verification

3.1.1 Uninterrupted sensor function

The uninterrupted recording function was tested and

verified by a water-jacketed recharging test. The test involved

putting the sensor in a box full of water with a wireless

recharging table under the box (30 mm in height). The

hardware test setup is shown in Fig. 2(a). The battery voltage

was recorded to obtain a power consumption curve with the

wireless recharging table on or off; the resulting battery

voltage curves are shown in Fig. 2(b). Before the hardware test,

the battery was fully charged; its voltage was about 4.2 V.

When the recharging system was on, the voltage of the battery

was maintained above 3.7 V, indicating that the power

recharged was larger than the power consumed. When the

recharging system was off, the voltage decreased gradually,

following to below 3.7 V (working voltage) after about

24 hours. Overall, for WS-II, the power recharged was about

20 mW and the power consumed was about 12 mW, as

assessed by power meter. The temperature of WS-II was

recorded during recharging. Recharging did not affect the

temperature (Fig. 2(c)).


(a)

(b)

(c)

Figure 2. (a) Setup of the hardware test. WS-II, which is composed of

WS-I and a wireless recharging circuit, was placed in a box

full of water at a 30-mm height. The sensor was operated

continuously with the wireless recharging table either on or

off. The battery voltage was then measured. (b) Efficiency of

the 30-mm-water-jacketed recharge. (c) Temperature of the

sensor. The temperature was recorded during recharging and

during resting (no wireless recharge). The temperature curve

showed no difference between the two conditions.

(mean ± SEM, n = 5).

3.1.2 Long-term recording in freely moving rats

The long-term recording test was an in vivo experiment.

The sensor recorded continuously for ten days. The raw data

showing the rat’s EEG-p, EEG-o, EMG, ECG, and 3-axis

acceleration signals are presented in Fig. 3. In the AW stage,

there are high-frequency low-amplitude variations in the EEG

and high-activity variations in the EMG and 3-axis

accelerations. In the QS stage, there are low-frequency

high-amplitude variations in the EEG and low-activity

variations in the EMG and 3-axis accelerations. In the PS stage,

there are high-frequency low-amplitude variations in the EEG

and low-activity variations in the EMG and 3-axis

accelerations. The uninterrupted RR, TP, HF, LF, and LF/HF

data are presented in Fig. 4. The latter figure clearly shows the

presence of a circadian rhythm. There are regular fluctuations

present in each channel. The cycle time is about 24 hours. Rats

are nocturnal animals and therefore the RR and TP values

during the dark periods are much lower than those during the

light periods. Similarly, the HF, which represents

parasympathetic tone, increases during the light periods and

decreases during the dark periods. In contrast, the LF/HF ratio,

which represents sympathetic activity, decreases during the

light periods and increases during the dark periods. These

results are consistent with rats being more active during dark

periods. The LF, which is considered to represent both

sympathetic activity and parasympathetic tone, should

represent the circadian rhythm. The continuously recorded data

for LF indeed shows a typical circadian rhythm.

Figure 3. Raw data for the three stages. Seven channels (EEG-p, EEG-o,

EMG, ECG, and 3-axis accelerations) for the three stages (AW,

QS, and PS) are shown.

Figure 4. Uninterrupted 10-day recording data for ECG signals and

analysis of HRV. The black and white intervals represent dark

and light periods, respectively (08:00 AM to 08:00 PM lights

on). The five channels are R-R intervals (RR), total power

(TP), high-frequency power (HF), low-frequency power, and

LF to HF ratio (LF/HF) of HRV. There are regular

fluctuations matching the light-dark cycle within each

channel, and these approximately represent the circadian

rhythm.


3.2 Effect on rat physiology

3.2.1 Temporal variation in animals’ body weights

A body weight curve is considered by many to be an

indicator of health condition. Therefore, the body weights of

the animals in the three groups were recorded throughout the

experiment. A baseline weight value was obtained before

surgery. Differences between the animals’ weights at time

intervals during the experiment and the baseline weight were

calculated. All three groups showed a trend of weight increase

with time at a rate of about 4 g/day (Fig. 5). The body weights

of the control, sham, and experimental animals showed no

difference from the first day (control vs. sham vs. experimental:

16 ± 1.87 vs. 19 ± 2.45 vs. 15 ± 4.18, F = 0.48, p = 0.63) to the

tenth day (control vs. sham vs. experimental: 34 ± 3.32 vs.

36 ± 1.87 vs. 34 ± 2.92, F = 0.17, p = 0.84).

Figure 5. Change in body weight after implantation of sensor. The

differences between present body weight and the baseline

body weight (before surgery) were calculated. There were

similar trends for the control, sham, and experimental groups.

(mean ± SEM, n = 5)

3.2.2 Effect on sleep/wake patterns and physical activity

The sleep/wake patterns and physical activity of rats can

be changed by stress. Therefore, the parameters associated with

sleep/wake patterns and physical activity can be used as

quantitative indicators of stress. The sleep/wake patterns can be

characterized by three parameters, namely time, number, and

duration. Sample sleep/wake patterns and a physical activity

comparison for the first, fifth, and tenth days after the

recovering period are shown in Table 1. The parameters were

compared each day. The rat AW stages take up less time, are

fewer in number, and have shorter durations during the light

periods than during the dark periods. These differences are

representative of the distinct natures of the light and dark

periods in terms of sleep/wake patterns. The three groups

showed no difference in AW (F = 1.49, p = 0.27), QS (F = 1.71,

p = 0.41) and PS time (F = 0.60, p = 0.56) during the first light

period. There was also no difference during the fifth (AW:

F = 0.59, p = 0.57, QS: F = 0.44, p = 0.66, PS: F = 0.17,

p = 0.84) and tenth light periods (AW: F = 0.31, p = 0.74, QS:

F = 0.94, p = 0.42, PS: F = 0.45, p = 0.65). With regard to

physical activity, the three groups of animals did not behave

differently during AW (F = 0.54, p = 0.60), QS (F = 1.22,

p = 0.33), and PS (F = 0.21, p = 0.82) stages, respectively, of

the first light period. Also, no difference was seen during the

fifth (AW: F = 0.17, p = 0.83, QS: F = 0.66, p = 0.54, PS:

F = 0.13, p = 0.76) and tenth light periods (AW: F = 1.65,

p = 0.23, QS: F = 0.59, p = 0.57, PS: F = 0.15, p = 0.84). The

results were the same for the dark period (i.e., no difference in

sleep-wake cycles or physical activity). Moreover, from

observations of these animals (video recording), the animals

with the implant behaved as normally as those without the

implant. Thus, it was concluded that the sleep/wake patterns

and physical activities, and therefore stress, across the groups

were similar.

3.2.3 Effect on autonomic nervous functions

Autonomic nervous functions can represent the stress and/

or health of rats. The recorded autonomic nervous functions

during the experiment were compared each day. As examples,

the autonomic nervous functions (assessed by RR, HF, and

LF/HF) for the first, fifth, and tenth days after the recovery

period are shown in Table 2. Overall, the RR and HF values for

the dark periods are lower than those for the light periods. This

indicates that the rats had a faster heart rate in the dark than in

the light, and that there was greater parasympathetic tone in the

light than in the dark. However, the LF/HF ratio, which

represents sympathetic activity, did not show an obvious

difference between light and dark. Thus, the cardiac autonomic

functions across the three groups were all affected by circadian

rhythms.

The three groups showed no difference in AW (F = 0.15,

p = 0.86), QS (F = 0.44, p = 0.65), and PS RR (F = 0.24,

p = 0.79) during the first light period. There were also no

differences in RR during the fifth (AW: F = 0.59, p = 0.64, QS:

F = 0.10, p = 0.79, PS: F = 0.81, p = 0.45) and tenth light

periods (AW: F = 0.31, p = 0.74, QS: F = 0.65, p = 0.54, PS:

F = 0.64, p = 0.55). The HRV values were thus similar between

these animals. The three groups showed no difference in AW

(F = 0.56, p = 0.59), QS (F = 0.04, p = 0.97), and PS HF

(F = 0.62, p = 0.56) during the first light period, the fifth light

period (AW: F = 0.36, p = 0.71, QS: F = 1.50, p = 0.26 and PS:

F = 0.66, p = 0.46), and the tenth light period (AW: F = 0.10,

p = 0.90, QS: F = 1.05, p = 0.38 and PS: F = 0.01, p = 0.97).

No difference in LF/HF was found during AW (F = 1.38,

p = 0.29), QS (F = 0.33, p = 0.72), or PS (F = 0.52, p = 0.60)

stages in the first light period. The LF/HF ratio had no

differences between groups during the fifth (AW: F = 1.98,

p = 0.18, QS: F = 1.87, p = 0.45, PS: F = 0.41, p = 0.87) and

tenth light periods (AW: F = 1.34, p = 0.30, QS: F = 0.15,

p = 0.87, PS: F = 2.25, p = 0.15). For the dark period data, no

differences were found between groups in these cardiac

measures. It can be thus concluded that cardiac autonomic

functions were not affected by the implantable device.


Table 1. Comparison of sleep/wake states of rats. On the first, fifth, and tenth days after the recovery period, a sleep/wake data analysis of the control,

sham, and experimental rats was carried out. The sleep/wake patterns consist of three stages, namely active waking (AW), quiet sleep (QS),

paradoxical sleep (PS). The three parameters are accumulated time, number of events, and duration of events during the light period (top

sub-table) and during the dark period (bottom sub-table).

Light period 1

st day 5

th day 10

th day

Control Sham Experimental Control Sham Experimental Control Sham Experimental

Time

(min)

AW 156.96 ± 22.08 173.31 ± 20.41 144.67 ± 11.73 126.31 ± 12.83 131.64 ± 10.02 118.27 ± 8.26 128.93 ± 11.12 132.33 ± 11.94 135.10 ± 10.62

QS 377.00 ± 13.45 371.00 ± 5.77 387.73 ± 7.97 378.27 ± 17.59 375.27 ± 7.26 380.81 ± 5.10 404.00 ± 13.87 394.76 ± 6.46 398.22 ± 14.47

PS 183.86 ±10.57 172.41 ± 17.54 184.06 ± 8.16 196.84 ± 8.05 200.50 ± 5.43 209.00 ± 7.11 183.85 ± 7.77 189.15 ± 8.59 178.46 ± 10.81

Number (stages)

AW 14.71 ± 2.49 16.86 ± 1.77 14.18 ± 1.33 13.87 ± 1.54 15.73 ± 1.29 13.78 ± 0.91 13.18 ± 1.83 13.43 ± 1.61 14.74 ± 1.35

QS 47.86 ± 1.39 46.14 ± 0.86 48.09 ± 1.95 49.33 ± 2.13 51.68 ± 1.32 50.72 ± 1.38 48.64 ± 1.71 47.81 ± 1.49 48.22 ± 1.76

PS 41.86 ± 1.70 41.57 ± 2.24 44.09 ± 2.23 44.60 ± 2.16 45.64 ± 0.96 47.97 ± 1.33 43.55 ± 1.46 44.76 ± 1.10 42.87 ± 1.95

Duration

(min/stage)

AW 10.82 ± 1.16 10.29 ± 0.66 9.91 ± 1.05 10.05 ± 1.10 9.08 ± 0.81 9.77 ± 0.93 12.52 ± 1.59 12.12 ± 2.01 11.54 ± 1.66

QS 7.42 ± 0.21 7.28 ± 0.28 7.82 ± 0.23 8.24 ± 0.99 7.05 ± 0.37 7.33 ± 0.46 8.28 ± 0.68 7.84 ± 0.81 7.91 ± 0.52

PS 4.36 ± 0.14 4.30 ± 0.17 4.14 ± 0.24 4.17 ± 0.26 4.34 ± 0.29 4.13 ± 0.28 4.08 ± 0.14 4.08 ± 0.19 4.04 ± 0.40

Physical

activity

(gravity)

AW 0.37 ± 0.06 0.45 ± 0.08 0.40 ± 0.08 0.56 ± 0.06 0.46 ± 0.06 0.50 ± 0.06 0.51 ± 0.08 0.45 ± 0.03 0.52 ± 0.05

QS 0.02 ± 0.01 0.03 ± 0.01 0.03 ± 0.01 0.02 ± 0.01 0.02 ± 0.01 0.03 ± 0.00 0.02 ± 0.01 0.02 ± 0.01 0.02 ± 0.01

PS 0.06 ± 0.02 0.06 ± 0.03 0.06 ± 0.02 0.05 ± 0.03 0.07 ± 0.03 0.08 ± 0.04 0.05 ± 0.02 0.06 ± 0.01 0.10 ± 0.03

Dark period 1

st day 5

th day 10

th day


Time

(min)

AW 316.78 ± 14.79 324.46 ± 15.26 295.97 ± 21.54 283.95 ± 22.68 308.64 ± 18.50 288.91 ± 25.43 278.48 ± 10.23 266.64 ± 26.30 274.80 ± 27.45

QS 289.00 ± 8.98 287.78 ± 19.84 301.34 ± 12.42 302.75 ± 33.72 292.99 ± 20.91 300.48 ± 22.93 295.98 ± 23.82 310.53 ± 22.99 305.35 ± 22.22

PS 106.49 ± 8.91 97.92 ± 5.36 109.84 ± 8.07 115.97 ± 16.82 100.33 ± 11.01 119.09 ± 16.00 126.93 ± 11.81 120.74 ± 17.57 121.92 ± 9.17

Number

(stages)

AW 26.44 ± 1.75 26.17 ± 1.53 24.33 ± 2.40 25.75 ± 1.60 24.54 ± 1.48 23.75 ± 2.25 25.50 ± 2.10 22.05 ± 2.95 23.50 ± 2.17

QS 46.33 ± 2.97 46.58 ± 2.72 45.44 ± 4.25 35.75 ± 4.01 38.07 ± 3.34 39.38 ± 4.57 40.25 ± 4.61 42.95 ± 2.74 39.33 ± 5.48

PS 34.44 ± 2.52 27.25 ± 1.67 33.89 ± 3.75 33.25 ± 3.47 32.86 ± 3.21 34.25 ± 7.10 29.50 ± 6.59 33.05 ± 1.91 35.67 ± 5.39

Duration (min/stage)

AW 12.63 ± 1.19 12.58 ± 0.47 12.32 ± 1.32 13.87 ± 0.62 13.19 ± 1.04 12.66 ± 1.61 13.63 ± 1.27 13.22 ± 1.61 12.12 ± 0.93

QS 6.61 ± 0.38 6.60 ± 0.83 6.69 ± 0.25 6.91 ± 0.65 6.66 ± 0.45 5.89 ± 0.26 5.76 ± 0.41 6.22 ± 0.93 5.95 ± 0.60

PS 2.85 ± 0.11 2.92 ± 0.17 3.15 ± 0.11 3.28 ± 0.26 3.32 ± 0.32 3.24 ± 0.54 3.27 ± 0.19 3.96 ± 0.36 3.56 ± 0.31

Physical

activity

(gravity)

AW 0.55 ± 0.03 0.51 ± 0.04 0.50 ± 0.05 0.55 ± 0.03 0.47 ± 0.04 0.51 ± 0.06 0.54 ± 0.04 0.55 ± 0.03 0.60 ± 0.05

QS 0.03 ± 0.01 0.03 ± 0.01 0.03 ± 0.01 0.05 ± 0.01 0.03 ± 0.03 0.04 ± 0.01 0.03 ± 0.00 0.01 ±0.00 0.03 ± 0.01

PS 0.08 ± 0.02 0.07 ± 0.04 0.10 ± 0.03 0.11 ± 0.05 0.09 ± 0.06 0.14 ± 0.06 0.10 ± 0.03 0.12 ± 0.02 0.15 ± 0.04

Table 2. Comparison of autonomic nervous functions. On the first, fifth, and tenth days after the recovery period, a HRV data analysis of the control,

sham, experimental rats was carried out. The autonomic nervous functions as assessed by HRV were considered for AW, QS, and PS stages

and described using three autonomic parameters, namely RR intervals (RR), high-frequency power (HF) of the HRV, and low-frequency

power to high-frequency power ratio (LF/HF) of the HRV. These were analyzed for the light period (top sub-table) and for the dark period

(bottom sub-table).

Light period 1st day 5th day 10th day


RR

(ms)

AW 176.19 ± 2.78 171.34 ± 3.02 173.13 ± 3.81 186.22 ± 2.14 184.27 ± 3.08 183.88 ± 1.61 182.13 ± 1.23 182.22 ± 1.79 184.87 ± 5.83

QS 204.80 ± 2.85 207.43 ± 5.16 203.77 ± 4.83 219.41 ± 2.57 220.85 ± 5.35 215.00 ± 3.73 222.12 ± 1.56 223.16 ± 2.15 223.39 ± 5.33

PS 218.05 ± 3.93 210.09 ± 5.07 202.77 ± 5.29 218.31 ± 3.03 221.41 ± 7.16 215.16 ± 3.81 215.32 ± 2.74 216.37 ±3.99 213.46 ± 5.15

HF

[ln(ms2)]

AW 0.42 ± 0.08 0.45 ± 0.08 0.39 ± 0.10 0.64 ± 0.11 0.64 ± 0.13 0.56 ± 0.12 0.95 ± 0.13 0.97 ± 0.20 0.81 ± 0.11

QS 0.87 ± 0.15 0.88 ± 0.18 0.91 ± 0.06 0.74 ± 0.16 0.72 ± 0.08 0.89 ± 0.08 0.58 ± 0.13 0.62 ± 0.19 0.64 ± 0.15

PS 1.18 ± 0.18 1.20 ± 0.10 1.07 ± 0.06 1.21 ± 0.11 1.13 ± 0.10 1.27 ± 0.05 0.89 ± 0.10 0.93 ± 0.15 1.11 ± 0.20

LF/HF

[ln(ratio)]

AW 1.86 ± 0.04 1.72 ± 0.11 1.77 ± 0.15 1.62 ± 0.17 1.59 ± 0.11 1.57 ± 0.14 1.92 ± 0.03 1.90 ± 0.04 1.85 ± 0.05

QS 0.18 ± 0.12 0.16 ± 0.14 0.20 ± 0.18 0.26 ± 0.15 0.20 ± 0.06 0.18 ± 0.05 0.75 ± 0.08 0.66 ± 0.10 0.67 ± 0.13

PS 1.30 ± 0.10 1.21 ± 0.06 1.15 ± 0.15 1.20 ± 0.19 1.17 ± 0.10 1.07 ± 0.13 1.90 ± 0.07 1.87 ± 0.10 1.73 ± 0.16

Dark period 1st day 5th day 10th day


RR

(ms)

AW 172.79 ± 2.29 173.18 ± 1.59 177.24 ± 3.20 174.99 ± 4.70 172.62 ± 3.27 177.75 ± 2.92 172.35 ± 2.80 174.28 ± 2.51 173.18 ± 3.92

QS 211.99 ± 3.47 211.98 ± 2.99 209.74 ± 2.74 209.48 ± 5.44 208.39 ± 3.55 205.41 ± 4.05 206.14 ± 3.51 212.85 ± 3.37 207.24 ± 2.80

PS 208.41 ± 2.92 211.33 ± 2.80 207.83 ± 3.74 198.07 ± 7.40 203.63 ± 4.20 204.71 ± 1.93 196.95 ± 5.57 203.90 ± 3.61 198.55 ± 3.60

HF

[ln(ms2)]

AW 0.41 ± 0.13 0.32 ± 0.07 0.41 ± 0.10 0.87 ± 0.05 0.72 ± 0.11 0.91 ± 0.14 0.52 ± 0.09 0.62 ± 0.06 0.60 ± 0.05

QS 1.34 ± 0.15 1.28 ± 0.09 1.36 ± 0.16 1.11 ± 0.15 1.26 ± 0.07 1.22 ± 0.23 1.26 ± 0.10 1.29 ± 0.06 1.30 ± 0.16

PS 1.38 ± 0.13 1.43 ± 0.09 1.39 ± 0.12 1.31 ± 0.13 1.24 ± 0.08 1.34 ± 0.20 1.02 ± 0.18 1.18 ± 0.16 1.06 ± 0.11

LF/HF

[ln(ratio)]

AW 1.59 ± 0.07 1.64 ± 0.08 1.55 ± 0.08 1.68 ± 0.05 1.61 ± 0.06 1.64 ± 0.10 1.65 ± 0.05 1.54 ± 0.03 1.64 ± 0.11

QS -0.08 ± 0.14 -0.13 ± 0.06 0.09 ± 0.10 0.05 ± 0.10 -0.03 ± 0.08 -0.05 ± 0.13 0.16 ± 0.03 0.09 ± 0.07 0.13 ± 0.09

PS 1.07 ± 0.15 0.95 ± 0.06 1.11 ± 0.13 0.98 ± 0.09 1.01 ± 0.05 1.07 ± 0.10 1.15 ± 0.04 0.96 ± 0.07 0.96 ± 0.14


4. Conclusion

A wireless recharging technique was combined with a

wireless recording system for the uninterrupted recording of

animal sleep/wake patterns and autonomic nervous functioning

with minimal disturbance. The proposed system allows high-

frequency resolution of ultra-long rhythms to be obtained,

which is important for ultra-low frequency recordings. The

HRV variables were found to have an obvious circadian

rhythm.

The proposed uninterrupted wireless recording system has

some limitations. Firstly, the distance between the inductive

coil and wireless recharging table must be less than 35 mm,

because the strength of an alternating magnetic field decreases

with distance. Although the lithium-ion polymer battery can

provide uninterrupted power, allowing continuous recording,

the battery power is finite. If the animal remains outside the

charging distance for long enough, the recording will be

interrupted. Behaviors that increase the distance between the

implant and the recharge table or make the horizontal plane of

the coil not parallel with the recharge table, like rearing, reduce

recharging efficiency. These behaviors are not numerous

( < 20% of the experimental period) and the wireless

recharging function work well over 80% at a daily scale.

Some aspects of the wireless system need improvement.

Firstly, the wireless transmission distance has to be increased.

Secondly, an improvement in the rate of wireless data

transmission is needed, which will require novel RF integrated

circuits, techniques, and devices to be developed. Thirdly, there

is a need to reduce the sensor size and weight. This can be

achieved using microelectromechanical systems technology.

Fourthly, to better determine the biological effects of the

implantable device, the effects on tissue should be analyzed.

Future electrophysiological research is likely to target social

behavior interactions in rats as a group, the effect of particular

conditions, such as restricted space, on rat electrophysiology,

and ultra-low frequency analysis of electrophysiological data

over a rat’s complete lifespan.

Acknowledgements

This study was supported by a grant (YM-99A-C-P506)

from the Ministry of Education, Aim for the Top University

Plan, and a grant (NSC 99-2314-B-010-014) from the National

Science Council (NSC), Taiwan. The authors would like to

thank Mr. Chi-Hao Mak for his skillfully surgery of the rats and

Ms. Ying-Hua Huang for editing the manuscript.

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