WO2009138923A1

WO2009138923A1 - A method and apparatus for measuring and reducing mental stress

Info

Publication number: WO2009138923A1
Application number: PCT/IB2009/051892
Authority: WO
Inventors: Harald Reiter; Robert Pinter; Gerhard Spekowius; Donghai Yu; Joerg Habetha; Jens Mulsteff; Sandrine Magali Laure Devot; Xavier Louis Marie Antoine Aubert
Original assignee: Koninklijke Philips Electronics N.V.; Philips Intellectual Property & Standards Gmbh
Priority date: 2008-05-12
Filing date: 2009-05-08
Publication date: 2009-11-19

Abstract

The present invention proposes an apparatus and method for measuring the user's mental stress level. The apparatus comprises a first measuring unit for measuring a heart rate variability (HRV) signal of a user; a second measuring unit for obtaining a respiration signal of the user; and a processing unit for generating an indicative signal representing the user's mental stress level in dependence on the obtained respiration signal and the measured HRV signal.

Description

A METHOD AND APPARATUS FOR MEASURING AND REDUCING MENTAL STRESS

Field of the Invention The present invention relates to a method and apparatus for measuring and reducing a user's mental stress, and in particular to a method and apparatus capable of accurately measuring and effectively reducing the mental stress level of the user.

Background of the Invention Nowadays, much pressure is imposed on individuals by heavy work, strong competition and ever increasing demands of life, among which the ever heavier workload is the most significant stress factor. For example, 70% of the employees in some developing areas report high stress levels, and 27% of senior managers describe themselves as being in a high burn-out condition. Excessive exposure to stress from work keeps people busy with work all day long, they have to consume fast food and have not enough sleep. This unhealthy lifestyle results in more stress and anxiety. Many people sleep badly and suffer from headache and endocrine disorders, while many of them are suffering higher levels of blood pressure and cholesterol caused by excessive pressure. Therefore, it is absolutely necessary for people in modern society to relieve themselves from work pressure and keep their peace of mind and a relaxed condition.

A number of devices are commercially available today which are supposed to help achieve relaxation. A simple embodiment is a CD playing relaxing sounds of nature, for example. There are also more sophisticated examples, for example, a system capable of providing "biofeedback" to the user. Such a system may, for example, take physiological measurements of parameters that change in dependence on the stress felt by the user, like heart rate, skin temperature or skin conductivity, while playing beautiful scenery slides and soothing music to the user. The system then provides the measured parameters to the user as "biofeedback" information, thus informing the user about his current stress status. Recently, a stress-relieving device has become commercially available that provides the

Heart Rate Variability (HRV) as "biofeedback" information to the user. In addition to the parameters mentioned above, the device also measures and calculates the user's HRV according to the RR interval extracted from the ECG (electrocardiograph) and estimates from this the stress level of the user according to the HRV.

Heart rate variability (HRV) relates to the beat-to-beat alterations in the heart rate. Research shows that the heart rate of healthy individuals exhibits a periodic variation under resting conditions, and the more relaxed the individual, the wider the variation. By contrast, the heart rate variation of healthy individuals is comparatively small and may be considered constant under stressed conditions. The stress-relieving device estimates the stress level of the user on the basis of this HRV characteristic of the user. However, errors may occur in such a stress-relieving device when it estimates the user's mental stress level. This is because HRV is influenced by many factors, for example the HRV of a heart disease patient may change considerably. An estimation of the user's mental stress level only by means of HRV is not as accurate as desired.

Furthermore, the above currently available stress-relieving devices either display the measured parameters (e.g., skin conductivity) to the user directly or present an abstract mental stress level, such as "mental stress level 5" obtained by computation, to the user. These values are not straightforward enough for the user to understand; he/she cannot judge his/her physical condition from the feedback values. Therefore, it is also desirable to develop a device that can provide plain feedback information to help the user to appraise his/her physical condition.

Summary of the Invention

An objective of the present invention is to provide a method and apparatus that can accurately estimate the user's mental stress level. Another objective of the present invention is to provide a method and apparatus that can provide straightforward feedback indicating the mental stress level to the user.

According to an aspect of the present invention, it provides an apparatus for measuring the user's mental stress level. The apparatus comprises a first measuring unit for measuring a heart rate variability (HRV) signal of a user; a second measuring unit for obtaining a respiration signal of the user; and a processing unit for generating an indicative signal representing the user's mental stress level in dependence on the obtained respiration signal and the measured HRV signal. According to another aspect of the present invention, it provides a method of measuring the user's mental stress level. The method comprises the steps of: measuring a heart rate variability (HRV) signal of a user; obtaining a respiration signal of the user; and generating an indicative signal representing the user's mental stress level in dependence on the HRV signal and the respiration signal.

The other objectives and advantages of the present invention as well as a better understanding of the present invention will be obtained from a perusal of the following description, which is given with reference to the drawing and the claims.

Brief Description of the Drawings

The present invention will be described below with reference to examples and the accompanying drawings, wherein,

Fig. 1 gives the time domain and frequency domain diagrams of the HRV signal and the respiration signal under different mental conditions, according to an embodiment of the present invention;

Fig. 2 shows a block diagram of a stress-reducing apparatus according to an embodiment of the present invention;

Fig. 3 is a diagram of the process of analyzing the HRV signal and the respiration signal in the time domain, according to an embodiment of the present invention; Fig. 4 is a flow chart of a time domain analysis according to an embodiment of the present invention;

Fig. 5 is a block diagram of a stress-reducing apparatus according to another embodiment of the present invention;

Fig. 6 shows a design of a stress-reducing apparatus according to another embodiment of the present invention; and

Fig. 7 is a schematic diagram of pulse arrival time according to an embodiment of the present invention.

Throughout the drawings the same reference numerals indicate similar or identical features or functions.

Detailed Description of the Invention Fig. 1 illustrates a comparison between the HRV signal and the respiration signal under stressed and resting conditions, wherein the graph on the left is the time domain signal and that on the right is the power spectral density distribution each time. As shown in Fig. 1, the HRV of a healthy individual exhibits a clear period under relaxing conditions, e.g. while asleep, and the HRV follows the phase of respiration: cardio-acceleration during inhalation, and cardio-deceleration during exhalation. This rhythmic HRV is known as the respiratory sinus arrhythmia (RSA). As the graphs on the right of Fig. 1 also show, the power spectrum of HRV exhibits a narrow, high spike near the peak frequency of the respiration signal under resting conditions due to its periodicity. Under stressed conditions, by contrast, there is little variation and no obvious periodicity present in the user's HRV. According to the variation characteristic of the HRV signal versus the respiration signal as shown in Fig.l, an embodiment of the present invention is proposed for estimating the user's mental stress level of by combining the respiration signal and the HRV signal. The First Embodiment Fig. 2 is a block diagram of a stress-reducing apparatus 100 according to an embodiment of the present invention. As shown in Fig. 2, the stress-reducing apparatus 100 includes an HRV measuring unit 110, a respiration measuring unit 120, a processing unit 130, and a display unit 140. The processing unit 130 is configured to estimate a user's mental stress level (MSL) in dependence on the HRV signal and the respiration signal obtained from the units 110 and 120, and then to generate guidance instructions on relaxation exercises (such as breathing exercises) for the user. The display unit 140 is configured to display the estimated MSL and the generated instructions to the user. For example, the display unit 140 may show or play pictures, music, or video while displaying the MSL so as to guide the user to breathe slowly and deeply in the frequency set by the guidance instructions. The detailed structure and operating procedure of the stress-reducing apparatus 100 according to the embodiment of the present invention will be described in more detail with reference to the drawings.

In Fig. 2, the HRV measuring unit 110 specifically comprises an electrocardiograph (ECG) sensor 111 for sensing a user's cardiovascular signals and an HRV extractor 115. The HRV extractor 115 extracts the R-R interval (an interval between successive heart beats) from the ECG signals sensed by the ECG sensor 111, thus acquiring an R-R interval sequence. In the HRV extractor, the R-R interval sequence can be transformed into, for example, an HRV signal in beats per minute (BPM), an example of which is shown as a time domain graph of the HRV signal on the left of Fig. 1.

While measuring the HRV signal, the stress-reducing apparatus 100 shown in Fig. 2 is also configured to obtain the user' s breathing signals by using the respiration measuring unit 120. In this embodiment, one or more accelerometers 121 are attached to the user's chest or the area close to the stomach, so that these accelerometers can be used to detect the movement of the chest or stomach while the user is breathing. Thus, the signals measured by the accelerometers 121 can represent the breathing frequency as well as the start and the end of the inhalation and exhalation phases. The measured signals from the accelerometers 121 are then transmitted to the respiration signal extractor 125 in a wired or wireless way so as to extract the respiration signal (RESPI) varying over time. The respiration measuring unit 120 may alternatively measure the user's respiration signal by using other sensors. For example, an air flow sensor or sound sensor arranged near the user's nose may alternatively be used to measure the respiration signal successfully. The respiration signals may also be detected by means of bio-impedance sensors detecting the change of the electricity axis caused by the breathing movement. Generally, only smooth respiration signals can be used to estimate the user' s MSL in this embodiment. Thus, the respiration signals sensed by the sensors may also be used to determine whether the user's breath is smooth. If the user's breathing is irregular, the respiration signals measured by sensors such as the accelerometers will not be used to compute the user's MSL; instead, the user will be prompted to breathe more regularly.

The HRV signal and the respiration signal (RESPI) measured by the units 110 and 120 are then fed to the processing unit 130 for further processing so as to estimate the user's mental stress level (MSL). In the embodiment shown in Fig. 2, the processing unit 130 can estimate the MSL by performing a time domain or frequency domain analysis on HRV and RESPI.

Time domain analysis

In the following, an exemplary description will be given of the time domain analysis on the HRV signal, the amplitude of which varies under the phase constrain of the breathing phase, cf. Figs. 3 and 4. Fig. 3 shows an HRV signal (upper) and a respiration signal (lower) measured in two respiration cycles by the units 110 and 120 while the user is at rest. Fig. 4 is a flowchart of a time domain analysis of the signals shown in Fig. 3 in the processing unit 130. As shown in Fig. 4, each time new HRV data, such as HRVl, HRV5 or HRV9 shown in Fig. 3, are read in the processing unit 130 (step S410), the latter determines whether the respiration signal corresponding to the data read in is in an inhalation phase, an exhalation phase or in a transition time (TT) between the inhalation and exhalation (step S420). If it is determined that the HRV data (e.g. HRVl) is in the inhalation phase, then the HRV data (e.g.

HRVl) is stored in an inhalation phase data pool (step S430). If it is determined that the HRV data (e.g. HRV9) relate to the exhalation phase, these data (e.g. HRV9) are stored in an exhalation phase data pool (step S450). If it is determined that the HRV data are merely in the transition time (TT) between inhalation and exhalation or between exhalation and inhalation (step S440), said data (e.g. HRV5) will be stored in both the inhalation phase data pool and the exhalation data pool, such that an error is avoided. The steps S410 to S450 are repeated until all of the HRV data in one complete respiration cycle have been stored in the data pools (step S460).

After storing the HRV data, the processing unit 130 finds the highest HRV (Max) (e.g. HRV5) from the inhalation phase data pool and the lowest HRV (Min) (e.g. HRV9) in the exhalation phase data pool and calculates the corresponding MSL according to the difference (Max-Min) (step S470). For example, if the difference is lOBpm, then MSL=I, which indicates that the user is comnparatively relaxed; if the difference is lBpm, then MSL=5, which indicates that the user is relatively stressed. Besides, if the difference is smaller than O', the negative value may be used as an indicator showing that the user is so stressed that his

HRV does not follow the breathing at all. Or, the negative value may also be an indicator showing that the respiration signal is not valid. For example, it may determine whether the respiration signal is valid by comparing the HRV difference quotient between the inhalation/exhalation phases or the HRV non-difference quotient. According to the flow shown in Fig. 4, the processing unit 130 can estimate the user's

MSL from the HRV signal and the respiration signal. However, the estimation of MSL in the processing unit 130 is not limited to the case shown in Fig. 4. For example, in certain simplified embodiments, HRV data may be stored in the inhalation/exhalation phase data pool directly without considering the above introduced transition term (TT) between inhalation and exhalation. It is also possible in the above embodiment to exclude the effect of noise by identifying and eliminating the "isolated extreme" (e.g. define the threshold of the difference between the largest (lowest) value and second largest (lowest) value). Alternatively, furthermore, the processing unit 130 may also calculate the deviation (i.e. the phase difference) between the HRV signal curve and the respiration signal curve by means of curve fitting when performing the time domain analysis. Specifically, the processing unit 130 may perform curve fitting on both the HRV signal curve and the respiration signal curve in e.g. a time window with a length of 2 breathing cycles, and then compare the deviation, i.e. the phase difference, between the fitted curves. The phase difference may be expressed as a percentage or in degrees. To make the result more accurate, a time deviation compensation window is defined, e.g., [0, min (2second, 0.25*breathing cycle)], and applied before the calculation of the deviation. When calculating the deviation, the HRV curve can slide in this time window and find the position that best fits the respiration curve, thus obtaining a minimum phase difference. The processing unit 130 then determines the corresponding MSL from the minimum phase difference. The computed phase difference may also be used as a signal quality indicator. For example, if the phase difference is high, it is indeed more likely that a lot of fakes are present in the HRV signal or the user's breathing is not smooth. Frequency domain analysis

In the above, a detailed description of a time domain analysis of the HRV and respiration signals performed by the processing unit 130 was given with reference to Figs. 2 to 4. Alternatively, the processing unit 130 may estimate the user's MSL by performing a frequency domain analysis on the measured HRV and respiration signals. When performing the frequency domain analysis, the processing unit 130 first obtains the power spectrums for both the HRV signal and the respiration signal within a pre-defined time window (e.g. 16 respiration cycles), for example by means of a Fourier Transform as shown in Fig. 1. The processing unit 130 next finds the power peak frequency Fr of the respiration signal in the power spectrum of the respiration signal. Next, the processing unit 130 finds the HRV power peak position nearest to the power peak frequency Fr of the respiration signal. For the example in Fig.l, it is assumed that the power peak frequency of the respiration signal Fr=O.13Hz. As shown in the HRV power spectrum, under resting conditions, the power peak frequency Hr of the HRV which is closest to the peak frequency Fr, is 0.14Hz; whereas under stressed conditions the Hr closest to Fr is 0.1 IHz. Based on the above, the processing unit 130 can now determine the user's MSL by computing the difference between the peak frequency Hr of the HRV signal and the peak frequency Fr of the respiration signal. The larger the difference, the higher the MSL. In addition, the amplitude of the HRV power peak closest to the peak frequency Fr of the respiration signal can also be used as an auxiliary reference for computing the MSL. For example, if the peak frequencies Hr and Fr are substantially identical, it holds that the flatter the HRV power peak, the higher the MSL, i.e. the more stressed the user; whereas a higher HRV power peak indicates a lower MSL.

Weighting Factor

Alternatively, the processing unit 130 may also correct the MSL thus obtained only according to the HRV, by using the comparison between the HRV and respiration signals, e.g. the phase difference or deviation between frequency spectrums, as weighting factors. For example, the processing unit 130 may first obtain the statistical data of the HRV signal by a conventional method. For example, the processing unit 130 may obtain statistical data of the HRV according to any of the following equations:

SDNN (standard deviation of heart beat intervals)

RMSSD (the root mean square of differences of successive heartbeat intervals)

RMSSD = SZ(RR₁ - RR₁^ IN pNN50 (percentage value of consecutive heartbeat intervals that differ by more than 50 ms)

/?ΛW50 = ^-^ - 100% N - I Next, the processing unit 130 may obtain the phase difference between the HRV and respiration signals or the deviation between their power spectrums by the above time domain or frequency domain analysis method. Finally, the processing unit 130 multiplies a weighting factor computed, for example, from the phase difference obtained through time domain analysis by a pre-computed HRV statistical value, thereby obtaining the final MSL. Here it holds for the mental stress level MSL: the greater the phase difference between the HRV and respiration signals, the higher the weighting factor. Thus the final MSL computed by the processing unit 130 can indicate the user's mental condition more accurately, since the MSL obtained according to the HRV is corrected by using the characteristic that the HRV follows the respiration signal. In the above, the structure and operating procedure of a stress-reducing apparatus according to an embodiment of the present invention was described with reference to the drawings. In this embodiment, the user can obtain an accurate and timely MSL when practicing relaxation exercises according to guidance instructions, since the stress-reducing apparatus can estimate the user's MSL from the characteristic that the HRV signal changes in dependence on the respiration signal.

The Second Embodiment

Fig. 5 shows a stress-reducing apparatus 200 according to another embodiment of the present invention. In contrast to the stress-reducing apparatus 100 shown in Fig. 2, the apparatus 200 shown in Fig. 5 is supplemented with a blood pressure (BP) measuring unit 250 for measuring the user's blood pressure. As Fig. 5 further shows, the respiration signal extractor 225 can generate a corresponding respiration signal in accordance with the respiration frequency in the guidance instructions when the user breathes according to the guidance instructions outputted from the processing unit 230,. Thus it differs from Fig. 2 in that the accelerometer 121 in the respiration measuring unit 220 is optional. Apart from the above modification, the other components of the stress-reducing apparatus 200 are the same as those of the apparatus 100 shown in Fig. 2, i.e. the apparatus 200 can compute and display an accurate MSL while presenting relaxation guidance instructions similar to the first embodiment.

Fig. 6 schematically illustrates a design of the apparatus 200. As shown in Fig. 6, the center part of the apparatus 200 is a display section of the display unit 240, which is configured to display data, instructions, charts, pictures, or video to the user. For example, the concentric circles in the center part of the apparatus 200 are used to display the guidance instructions for guiding the user to breathe regularly in accordance with the variation of the circles' color. Furthermore, handles 620 on both sides of the apparatus 200 are used as the probes of the ECG sensor 111 included in the HRV measuring unit 110. The touch section 610 on the upper right corner of the apparatus 200 is used as the probe of the PPG sensor 251 included in the BP measuring unit 250 shown in Fig. 5. When the user uses the apparatus 200, both the user's hands holding the handles 620, while a finger of his right hand rests on the touch section 610, then the ECG sensor 111 and PPG sensor 251 can simultaneously measure the user's ECG signal and PPG signal (as shown in Fig. 7) and have the signals transmitted to the PAT extractor 251 of the BP measuring unit 250. The PAT extractor 251 can then compute the time difference between the R peak of the ECG signal and the peak of the PPG signal from the received signals, as shown in Fig. 7. This time difference indicates the pulse arrival time (PAT) as well as the user's blood pressure condition. The computed PAT data are then applied to the processing unit 230. The processing unit 230 can convert the PAT data into blood pressure data and display these to the user via the display unit 240. As Fig. 6 shows, the blood pressure index under the current conditions is 6.

A description of the operating procedure of the BP measuring unit was given above by way of example. The BP measuring unit shown in Fig. 5 can be realized in a plurality of ways. For example, the probe of the PPG sensor in the example of Fig. 5 may be arranged at a different part of the body, e.g. on the auricle. In another example, the BP measuring unit may measure the PAT by means of a bio-impedance sensor/PPG sensor arranged in two different locations on the body. Alternatively, a bio-impedance sensor may be used to replace the PPG sensor 251 to measure the PAT in conjunction with the ECG sensor. It can be seen from the above that the display unit 240 in the apparatus 200 can not only display the MSL computed from the HRV signal and respiration signal, but also present the BP data to the user. Generally, the blood pressure tends to increase when people are nervous, so the BP data may also reflect the user's mental stress condition in a straightforward way. Moreover, blood pressure data are a physical parameter known to most people, thus helping the user effectively to know his/her stress condition by presenting BP data to the user. Besides the BP index shown in Fig. 6, the computed real BP of the user may also be displayed to the user, so that he/she can view the BP condition directly and can thus immediately know the effect of the breathing relaxation exercise on the blood pressure.

Furthermore, the example in Fig. 5 also shows a simple way of obtaining the respiration signal. Specifically, if the user is breathing regularly in accordance with the guidance instructions, the user's respiration frequency may be considered as being substantially equal to the respiration frequency set in the guidance instructions. In this case, the sensor for measuring the user's respiration, such as the accelerometer 121, may be omitted. This implies, as Fig. 5 shows for the time domain analysis, that the respiration signal extractor 225 can acquire the respiration frequency directly from the guidance instructions issued by the processing unit 230, and then generate a sinusoidal respiration signal therefrom so as to feed the respiration signal to the pressing unit. A further simplification can be made for the frequency domain analysis, i.e. the respiration signal extractor 225 may directly take the respiration frequency set by the guidance instructions as the peak frequency Fr of the respiration signal and feed it to the processing unit 230 for computing the difference between the peak frequencies. After obtaining the respiration signal as above, the processing unit 230 in the example of Fig. 5 may compute the difference, such as phase difference or deviation between spectrums, between the HRV signal and the respiration signal by the method described in the first embodiment. If the computed difference signal is larger than a predefined threshold, e.g. the difference (Max-Min) is smaller than 0, it shows that the user is not breathing according to the guidance instructions. The processing unit 230 then prompts the user to breathe according to the guidance instructions via the display unit.

Alternatively, a sensor such as an accelerometer may also be arranged in the respiration measuring unit 220 in the example of Fig. 5 for simultaneously measuring the user's respiration signal. The respiration signal measured by the accelerometer may be used to determine whether the user's breath is smooth or whether the user is breathing according to the guidance instructions, so that the accuracy of the respiration signal for computing the MSL is guaranteed.

The above describes the embodiments of the present invention with reference to the drawing. It should be noted that the above embodiments are exemplary rather than limiting. Many alternative implementations can be designed based on the above embodiment. For example, subject to practical requirements, each measuring unit and processing unit in the above embodiments may be incorporated into a mental stress measuring module which may be integrated into other medical apparatuses. Another example is that the HRV extractor, PAT extractor, and respiration signal extractor in the above embodiment are incorporated into a single processing unit and implemented with a CPU.

A detailed description of the embodiments of the present invention was given above with reference to the drawing. It should be noted that the above embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. Therefore, the scope of protection of the present invention is defined by the appended claims. Moreover, in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim.

Claims

1. An apparatus, comprising: a first measuring unit (110) for measuring a heart rate variability (HRV) signal of a user; a second measuring unit (120, 220) for obtaining a respiration signal of the user; a processing unit (130, 230) for generating an indicative signal representing the user 's mental stress level according to the obtained respiration signal and the measured HRV signal.

2. The apparatus of claim 1, wherein the indicative signal is generated according to a deviation between frequency spectrums of the HRV signal and the respiration signal.

3. The apparatus of claim 2, wherein the deviation between frequency spectrums is determined according to a power peak frequency of the respiration signal and a power peak frequency of the HRV signal, wherein the power peak frequency of the HRV signal is a frequency of a power peak in the power spectrum of the HRV signal which is closest to the power peak frequency of the respiration signal.

4. The apparatus of claim 1, wherein the indicative signal is generated according to a phase difference between the HRV signal and the respiration signal.

5. The apparatus of claim 1, wherein the indicative signal is determined by computing an amplitude variation of the HRV signal during an inhalation phase and an exhalation phase of the respiration signal.

6. The apparatus of claim 5, wherein the indicative signal is determined according to a maximum value of the HRV signal during the inhalation phase and a minimum value of the HRV during the exhalation phase.

7. The apparatus of claim 6, wherein the HRV signal during a transition time between the inhalation and exhalation phases is used as a common signal for computing the respective maximum value and minimum value in the different phases.

8. The apparatus of any of claims 1 to 7, wherein the indicative signal is obtained by correcting the mental stress level determined according to the HRV signal with a weighting factor, which weighting factor is determined from the HRV signal and the respiration signal.

9. The apparatus of claim 1, wherein the processing unit further generates instructions for guiding the user to reduce mental stress according to the indicative signal, and the apparatus further comprises: a display unit (140, 240) for displaying the indicative signal and the instructions to the user.

10. The apparatus of claim 9, further comprises: a third measuring unit (250) for measuring blood pressure data of the user; and the display unit is further configured to display the measured blood pressure data to the user.

11. The apparatus of claim 9, wherein the instructions include a given breathing frequency for guiding the user to breathe regularly, and the second measuring unit is further configured to generate the respiration signal according to the given breathing frequency.

12. The apparatus of claim 9, wherein the display unit presents the instructions in an audible and/or visual way.

13. The apparatus of claim 10, wherein the third measuring unit includes at least one of a

PPG sensor and a bio-impedance sensor.

14. The apparatus of claim 1, wherein the second measuring unit includes at least one of an accelerometer, an air flow sensor, a sound sensor, and a bio-impedance sensor.

15. A method comprising the steps of: measuring a heart rate variability (HRV) signal of a user; obtaining a respiration signal of the user; generating an indicative signal representing the user 's mental stress level according to the HRV signal and the respiration signal.

16. The method of claim 15, wherein the generating step comprises: generating the indicative signal according to a phase difference between the HRV signal and the respiration signal.

17. The method of claim 15, wherein the generating step comprises: generating the indicative signal according to an amplitude variation of the HRV signal during an inhalation phase and an exhalation phase of the respiration signal.

18. The method of claim 15, wherein the generating step comprises: generating the indicative signal according to a deviation between frequency spectrums of the HRV signal and the respiration signal.

19. The method of any of claims 16 to 18, wherein the generating step comprises: correcting the mental stress level determined according to the HRV signal by using the phase difference between the HRV signal and the respiration signal or the amplitude variation of the HRV signal during the inhalation phase and the exhalation phase of the respiration signal.

20. The method of claim 15, further comprising the step of: displaying instructions for guiding the user to reduce mental stressto the user.

21. The method of claim 20, wherein the instructions include a given breathing frequency for guiding the user to breathe regularly, and the respiration signal is obtained from the given breathing frequency.

22. The method of claim 20, wherein the obtaining step comprises: sensing the user's respiration signal by means of a sensor, and the method further comprises the steps of: determining whether the obtained respiration signal shows that the user is breathing smoothly; discarding the measured respiration signal if the user is not breathing smoothly and guiding the user to breathe regularly.

23. The method of claim 15, comprises: measuring the user's blood pressure data; and displaying the measured blood pressure data to the user.