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Title:
METHODS AND APPARATUSES FOR SIGNAL DETECTION
Document Type and Number:
WIPO Patent Application WO/2019/134965
Kind Code:
A1
Abstract:
The present disclosure relates to a concept of signal detection. A first signal (315) indicative of a first biometric identifier is measured at a first body portion. A second signal (325) indicative of the first biometric identifier is measured at a different second body portion. It is detected (330) whether the first and second signal are measured on the same body based on a comparison (335) of the measured first and second signals.

Inventors:
EMBRECHTS, Hugo (Sony Europe LimitedZweigniederlassung Deutschland,Stuttgart Technology Center, Hedelfinger Str. 61 Stuttgart, 70327, DE)
BAILADOR DEL POZO, Gonzalez (Sony Europe LimitedZweigniederlassung Deutschland,Stuttgart Technology Center, Hedelfinger Str. 61 Stuttgart, 70327, DE)
TORFS, Dimitri (Sony Europe LimitedZweigniederlassung Deutschland,Stuttgart Technology Center, Hedelfinger Str. 61 Stuttgart, 70327, DE)
Application Number:
EP2019/050153
Publication Date:
July 11, 2019
Filing Date:
January 04, 2019
Export Citation:
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Assignee:
SONY CORPORATION (1-7-1 Konan Minato-ku, Tokyo, 〒108-0075, JP)
SONY EUROPE LIMITED (The Heights, Brooklands, Weybridge KT13 0XW, KT13 0XW, GB)
International Classes:
G06F21/32; H04W12/06
Attorney, Agent or Firm:
2SPL PATENTANWÄLTE PARTG MBB (Postfach 151723, München, 80050, DE)
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Claims:
Claims

(1) A method (300) of signal detection, the method comprising:

measuring (310), at a first body portion, a first signal (115; 315) indicative of a first biometric identifier;

measuring (320), at a different second body portion, a second signal (145; 325) indicative of the first biometric identifier;

detecting (330) whether the first and second signal are measured on the same body based on a comparison (335) of the measured first and second signals.

(2) The method (300) of claim 1, wherein measuring the first signal (115; 315) and/or the second signal (145; 325) comprises measuring a blood flow of the user.

(3) The method (300) of claim 1, wherein the first biometric identifier is the heart rate of the user.

(4) The method (300) of claim 1, further comprising

measuring, at the first body portion, a third signal (165) indicative of a second biometric identifier; and

authenticating the user, if the third signal (165) matches a stored signal and if the difference between the first and the second signal is below the predefined thresh old.

(5) The method (300) of claim 4, wherein measuring the third signal (165) comprises measuring a fingerprint pattern of the user.

(6) The method (300) of claim 1, wherein the second signal (145; 325) is measured ffe- quently via a user- wearable sensor device (100).

(7) The method (300) of claim 6, further comprising:

upon authenticating the user, keeping the user authenticated as long as the user- wearable sensor device (100) frequently measures the second signal (145; 325). (8) The method (300) of claim 1, wherein the first signal (115; 315) is measured at a fin ger.

(9) The method (300) of claim 1, wherein the second signal (145; 325) is measured at a wrist.

(10) A device (100) for signal detection, the device comprising:

at least one signal interface configured to receive a first signal (115; 315) indica tive of a first biometric identifier measured at a first body portion and to receive a sec ond signal (145; 325) indicative of the first biometric identifier measured at a different second body portion; and

a processor (150) configured to detect whether the first and second signal have been measured on the same body based on a comparison of the first and the second signal.

(11) The device (100) of claim 10, wherein at least one signal interface is further config ured to receive a third signal (165) indicative of a second biometric identifier meas ured at the first body portion,

wherein the processor (150) is configured to authenticate the user, if the third signal (165) matches a stored signal and if a difference between the first and the sec ond signal is below a predefined threshold.

(12) The device (100) of claim 11, comprising a second sensor (140) configured to fre quently measure, at the second body portion, the second signal (145; 325), wherein the processor (150) is configured to detect whether the user is wearing the device based on the second signal.

(13) The device (100) of claim 12, further comprising

a first sensor (110) configured to measure, at the first body portion, the first sig nal (115; 315) indicative of the first biometric identifier; and

a third sensor (160) configured to measure, at the first body portion, the third signal (165) indicative of the second biometric identifier. (14) The device (100) of claim 11, wherein the third signal (165) is indicative of a finger print pattern as the second biometric identifier.

(15) The device (100) of claim 10, wherein the first and the second signals are indicative of a heart rate as the first biometric identifier.

Description:
METHODS AND APPARATUSES FOR SIGNAL DETECTION

Field

The present disclosure relates to methods and apparatuses for signal detection and, more particularly, to methods and apparatuses for detecting and/or authenticating a user based on biometric identifiers.

Background

Signal integrity and/or user authentication is relevant to multiple fields. In computer sci- ence, for example, verifying a person's identity is often required to allow physical and/or logical access to confidential data or systems, such as micropayment systems. The ways in which someone may be authenticated fall into three categories, based on something the user knows (e.g., a password, personal identification number (PIN), challenge response (the user must answer a question, or pattern, etc.), something the user has (e.g., wrist band, ID card, security token, cell phone with built-in hardware or software token, etc.), and something the user is (e.g., fingerprint, retinal pattern, DNA sequence, signature, face, voice, unique bio- electric signals, or other biometric identifier). Authentication concepts can also combine two or more of the mentioned categories, wherein combinations usually lead to more security.

It is desired to provide signal integrity and/or user authentication concepts that provide an increased level of protection from misuse or malicious intrusion.

Summary

This need is met by methods and apparatuses in accordance with the independent claims. Advantageous embodiments are addressed by the dependent claims.

According to a first aspect, the present disclosure provides a method of signal detection. The method includes measuring a first signal indicative of a (first) biometric identifier or param eter at a first body portion and measuring a second signal indicative of the same biometric identifier/parameter at a different second body portion. The method further includes detect- ing whether the first and second signals are measured on the same body based on a compari son of the measured first and second signal.

According to a further aspect, it is provided a signal detection device. The device comprises at least one signal interface which is configured to receive a first signal indicative of a first biometric identifier/parameter measured at a first body portion and to receive a second sig- nal indicative of the first biometric identifier/parameter measured at a different second body portion. The device further comprises a processor which is configured to detect whether the first and the second signals have been measured on the same body based on a comparison of the measured first and second signals.

Brief description of the Figures

Some examples of apparatuses and/or methods will be described in the following by way of example only, and with reference to the accompanying figures, in which

Fig. 1A shows a schematic flow chart of a signal detection method according to an embodiment;

Fig. 1B shows a perspective view of a wrist-wearable device according to an embod iment;

Fig. 2 shows a side view of the wrist-wearable device of Fig. 1B; and

Fig. 3 shows a signal detection method according to an embodiment.

Detailed Description

Various examples will now be described more fully with reference to the accompanying drawings in which some examples are illustrated.

Accordingly, while further examples are capable of various modifications and alternative forms, some particular examples thereof are shown in the figures and will subsequently be described in detail. However, this detailed description does not limit further examples to the particular forms described. Further examples may cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.

According to a first aspect, the present disclosure provides a method of signal detection. A schematic flow chart of such a method 10 is shown in Fig. 1A.

The method 10 includes measuring Sl l a first signal indicative of a (first) biometric identi fier/parameter at a first body portion and measuring S12 a second signal indicative of the same biometric identifier/parameter at a different second body portion. The method 10 fur ther includes detecting S13 whether the first and second signals are measured on the same body based on a comparison of the measured first and second signal. If a difference between the first and the second signal is below a predefined threshold it can be assumed that the signals have been measured on the same body. In some embodiments, the method can addi- tionally or alternatively also be used for authenticating the user.

Measuring signals indicative of the same biometric identifier or parameter at different body portions can increase the level of protection from misuse or malicious intrusion during user detection and/or authentication. The person having benefit from the present disclosure will appreciate that there are various biometric identifiers to identify a person that can be meas- ured at different body portions or locations, such as unique biosignals signals or voice, for example. Examples of electric biosignals include Electroencephalography (EEG), Electro- cardiogram (ECG), Electromyogram (EMG), Mechanomyogram (MMG), Electrooculog- raphy (EOG), Galvanic skin response (GSR), or Magnetoencephalogram (MEG). Although in principle any of these electric biosignals qualifies as the biometric identifier, the present disclosure focusses on biometric identifiers/parameters which can be derived from blood flow measurements, such as the heart rate (pulse), for example. Other examples of possible biometric identifiers which can be derived from blood flow measurements are skin blood flow, blood velocity, coagulation, and vascular ageing. Adequate body portions are depend- ent on the biometric identifier of interest. For example, a heart rate or signals indicative thereof can be measured at multiple body portions, such as chest, wrist, neck, or ear(s), for example.

Both the first and the second signal are indicative of the same biometric identifier / parame- ter. In some embodiments, the first and the second signal can both be indicative of a bio- metric identifier/parameter which is derived from blood flow measurements at different body portions, such as the heart rate (pulse), for example. Additionally or alternatively, the time between consecutive heartbeats can be used to check if they were measured at the same body.

In some embodiments, the method 10 can additionally further include measuring S14, at the first body portion, a third signal which is indicative of a further second biometric identifier. The user can be authenticated S15 if the third signal matches a stored signal (e.g., a stored biometric identifier) and a difference between the first and the second signal is below a pre- defined threshold.

An example of the second biometric identifier is a fingerprint pattern of the user. In this case an adequate first body portion would be a finger or, to be more specific, a fingertip. Howev- er, other body portions, such as an ear, are also conceivable.

In some embodiments, the first signal can be measured less frequently than the second sig- nal. For example, while the first and/or the third signal can be measured at non- predetermined time instances, the second signal can be measured frequently on a regular basis, for example periodically. That is, the first and/or the third signal can be an isolated sketch of the first/second biometric identifier measured via a respective sensor at a certain time instant. Instead, the second signal can be a continuous monitoring signal indicative of the first biometric identifier measured with a related second sensor.

In some embodiments, measuring the first signal at the first body portion can temporally coincide with measuring the third signal at the first body portion. While the first signal is indicative of the first biometric identifier, the third signal is indicative of the second bio- metric identifier. In embodiments where the first body portion corresponds to a finger or fingertip, the first biometric identifier can be a biometric identifier/parameter derived from blood flow measurements at the finger/fingertip. The second biometric identifier can be a fingerprint pattern in such cases.

In some embodiments, the second signal can be measured continuously via a user-wearable sensor device, e.g., via a sensor device that is worn by the user on his/her body. Thus, the second sensor can be included in a chest belt, a wrist-band, or similar devices, for example attached to the ear(s). On the other hand, the first and/or the third signal can be measured with respective sensors which do not need to be attached to the user’s body. Instead, the first and/or the third sensor may be attached to a device or entity to which the user wants to get physical and/or logical access. In some embodiments, more or all sensors can be included in one user-wearable sensor device.

In some embodiments, the method can further include, upon authenticating the user, keeping the user authenticated as long as the user is wearing the user-wearable sensor device contin uously measuring the second signal. Thus, the user can remain authenticated as long as (s)he is wearing the sensor device. When (s)he takes off the sensor device authentication gets lost.

In some embodiments, measuring the first signal can include performing blood flow meas urements at a fingertip. For this purpose, a fingerprint scanner adapted to (additionally) measure the blood flow can be used. This can be done using non-invasive optical technolo gies based on DLS (Dynamic Light Scattering) or on photoplethysmography. For example, a DLS sensor or photoplethysmographic sensor (e.g. pulse oximeter) can be integrated into the fingerprint scanner. Such a fingerprint scanner can detect both the user’s fingerprint and his/her heart rate, for example. The person having benefit from the present disclosure will appreciate that in principle also other biometric sensors (e.g. a retina scanner) could be adapted to (additionally) measure the blood flow and hence the heart rate, for example. Thus, the first sensor device can be configured to measure two different biometric identifi ers, one of them being the same as the biometric identifier measured via the second signal.

In some embodiments, measuring the second signal can include measuring the user’s blood flow at a wrist. The heart rate can be derived therefrom, for example. For this purpose, a DLS sensor or photoplethysmographic sensor can be integrated into a wrist-wearable de vice, such as a wristband or a watch, for example. Apart from the fingertip or wrist, the ear is also an option for taking blood flow measurements.

In some embodiments, comparing the measured first and second signal can include a rather simple comparison of the two signals or a more sophisticated correlation. For example, if the first signal indicates a heart rate of 70 of contractions of the heart per minute (bpm) and the second signal does not differ from that by more than e.g. 5% (i.e. 70 + 3.5 bpm), it can be assumed that both signals have been measured at the same body. Signal correlation can involve more sophisticated correlations of the two signal courses.

According to a further aspect, it is provided a signal detection device which can carry out method 10. The device comprises at least one signal interface which is configured to receive a first signal indicative of a first biometric identifier measured at a first body portion and to receive a second signal indicative of the first biometric identifier measured at a different second body portion. The device further comprises a processor which is configured to detect whether the first and the second signals have been measured on the same body based on a comparison of the measured first and second signals.

In some embodiments, the device could be a wearable user device, such as a smart phone or a smart watch, for example. In a basic configuration the device does not contain any sensors itself and the at least one signal interface could be an interface allowing a wireless or wired connection to one or more remote sensor devices. In other example implementations, the device can comprise one or more (biometric) sensors itself. For example, it can comprise a first sensor configured to measure the first signal at the first body portion and/or a second sensor configured to measure the second signal at the second body portion.

In some embodiments, the device’s one or more interfaces can be configured to receive a third signal indicative of a second biometric identifier, wherein the third signal is also meas- ured at the first body portion. In this case, the processor can be configured to authenticate the user, if the third signal matches a stored signal (e.g. stored biometric identifier of the user) and if a difference between the first and the second signal is below a predefined threshold. The skilled person having benefit from the present disclosure will appreciate that the device itself can also comprise a third sensor configured to measure the third signal at the first body portion.

In some embodiments, the third signal can be indicative of a fingerprint pattern as the sec- ond biometric identifier. Thus, a corresponding third sensor can be configured to measure the fingerprint pattern at the first body portion.

In some embodiments, the first and the second signals can both be indicative of a heart rate as the first biometric identifier. The first and the second signals can be derived from respec- tive blood flow measurements at different body portions. As explained before, also other human biosignals signals are conceivable.

According to a further aspect, it is provided a system for signal detection. The system com prises a first sensor configured to measure a first signal indicative of a first biometric identi fier at a first body portion, a second sensor configured to measure a second signal indicative of the first biometric identifier at a different second body portion, and a processor config ured to detect whether the first and the second signals have been measured on the same body based on a comparison of the measured first and second signals. While in some em bodiments the sensors can be distributed among different devices, the sensors can also be integrated into a common device (e.g., a wearable) in other embodiments.

In some embodiments, the first sensor can be a heart rate sensor integrated into a fingerprint scanner (third sensor). Of course, the first sensor could also be a stand-alone heart rate sen sor. The first sensor can be associated with a device or entity to which the user wants to get physical and/or logical access, such as a building, a vehicle, a computer, or a smartphone, just to name a few examples.

In some embodiments, the second sensor can be a heart rate sensor integrated into a wrist- wearable device. Of course, the second sensor could also be worn at other body portions, such as the chest, the leg(s), or the neck, for example.

In some embodiments, the heart rate sensor integrated into the wrist-wearable device can be configured to frequently measure the second signal indicative of the heart rate. The proces sor can be configured to detect whether the user is wearing the wrist-wearable device based on the second signal. In this way, the person can remain authenticated while wearing the wrist-wearable device. If he/she unclasps the wristband, (s)he loses the authentication.

In some embodiments, the system can further comprise a third sensor configured to measure a third signal indicative of a second biometric identifier at the first body portion. The pro cessor is configured to authenticate the user, if the third signal matches a previously stored biometric identifier and if the difference between the first and the second signal is below the predefined threshold. In some embodiments, the first and the third sensor are integrated into a common device in order to measure the respective signals at the same body portion. Embodiments of the present disclosure can ensure that a person who authenticates using a certain first biometric identifier, such as fingerprint, for example, is the same that is wearing the wearable sensor device sensing a second biometric identifier, such as the heart rate, for example.

Fig. IB shows a perspective view of a (biometric) signal detection device 100 according to an example embodiment of the present disclosure. Fig. 2 depicts a principle side view of signal detection device 100.

In the illustrated example, the signal detection device 100 is a wrist-wearable device, such as a smart watch. Other wearable devices, such as hand-, chest- or head-wearable devices, are also conceivable.

Device 100 comprises a first (biometric) sensor 110 which is configured to measure a first (biometric) signal 115 at a user’s first body portion. The first signal 115 is indicative of a biometric identifier of the user. In the illustrated example, the first sensor 110 integrated into the device 100 is configured to perform a first blood flow measurement at a user’s fin gertip 120. Other body portions (e.g., thumb, eye, etc.) are conceivable as well. Based on the first blood flow measurement, the first signal 115 is generated from which the biometric identifier can be extracted. In the illustrated example, the first sensor 110 integrated into the device 100 is a non- invasive optical sensor using DLS or photoplethysmographic techniques to identify the user’s heart rate as the biometric identifier. For this purpose, the user may place his fingertip 120 on a first sensing surface 130 associated with the first sensor 110. The skilled person having benefit from the present disclosure will appreciate that reliably determining the user’s heart rate via blood flow measurements may take several seconds (e.g., 5s or lOs for taking several heart beats).

The example wrist-wearable device 100 also comprises a second (biometric) sensor 140 which is configured to measure a second (biometric) signal 145 at a different second body portion. Thereby the second signal 145 is indicative of the same biometric identifier (here, the user’s heart rate). In the illustrated example, the second sensor 140 is located on the in ner side of the device 100 facing the user’s wrist. This can be better seen from the side view of device 100 illustrated in Fig. 2. The skilled person having benefit from the present disclo- sure will appreciate that the location and implementation of the second sensor 140 can vary depending on the biometric identifier to be measured. Similarly to the first sensor 110 on the outer/upper surface of device 100, the second sensor can 140 can be configured to perform a second blood flow measurement at the user’s wrist. Based on the second blood flow meas- urement, the second signal 145 is generated from which the same biometric identifier can be extracted. Similarly to the first sensor 110, the second sensor 140 can be a non- invasive op- tical sensor using DLS or photoplethysmographic techniques to identify the user’s heart rate as the biometric identifier. As such, the sensors 110, 140 may comprise corresponding light emitting and photo detection circuitry (not shown).

Although both sensors 110, 140 are based on the same measurement principle in the illus- trated example, the skilled person having benefit from the present disclosure will appreciate that the sensor 110, 140 could also rely on different measurement principles to obtain the respective signals 115, 145. For example, one sensor could rely on optical measurements while the other sensor could rely on measuring electrical signals via electrodes.

As can be seen from the side view of Fig.2, device 100 further includes a signal processor 150 receiving the respective signals 115, 145 of the two sensors 110, 140 and being config ured to detect whether the first and second signals 115, 145 have both been measured on the same body. For this purpose, the processor 150 can be configured to compare the measured first and the second signals 115, 145. If the two signals 115, 145 do not differ by more than a predefined maximum threshold, it can be assumed that both signals 115, 145 stem from the same body. Furthermore, it may be preferable that the signals 115, 145 stem from re spective biometric measurements which have been performed substantially at the same time. In this way it can be ensured that they reflect the same body condition. Hence, the processor 150 can optionally also be configured to compare time stamps of the first and the second signals 115, 145 and to only compare the measurement results if their respective time stamps do not differ by more than a predefined temporal threshold.

Although, Figs. 1 and 2 depict an example device 100 with integrated biometric sensors 110, 140, the skilled person having benefit from the present disclosure will appreciate that sensor 110 and/or 140 could also be implemented remotely or distant from processor 150 in other embodiments and device 100 could merely include wireless or wired interfaces for the first and second signals 115, 145. Embodiments of the present disclosure propose measuring the same biometric identifier (here, heart rate) at different body locations via two respective sensors 110, 140. For exam ple, the first sensor 110 can be embedded in or co-located with a fingerprint scanner to measure the heart rate in the fingertip 120. While the first sensor 110 is integrated into the wearable device 100 in the illustrated example, the skilled person having benefit from the present disclosure will appreciate that the first sensor 110 could also be an external sensor communicating with processor 150 via a wired or wireless communication interface. In the illustrated example, the second sensor 140 is attached to the back part of the wrist-wearable device 100 to measure the heart rate in the wrist. Both sensors 110, 140 could be based on photoplethismography, illuminating the user’s skin with a green, red or infrared light (de pending on the body location and skin color) and measuring the changes in reflection due to the blood volume (Blood Volume Pulse). Thus, both sensors 110, 140 can include LEDs and/or photodetectors, such as photodiodes. The hemoglobin absorbs the emitted light. Thus, when there is blood, the light reflected will be less intense.

The skilled person having benefit from the present disclosure will appreciate that other body locations and/or biometric sensors, for example based on ultrasound or electric resistance, could also be used for measuring the heart rate and blood flow.

In the illustrated example, the signals 115, 145 from both sensors 110, 140 are acquired by the processor 150 in the wrist-wearable device 100 and processed by processor 150. Usually these signals are noisy, so it might be beneficial to have a preprocessing stage to remove the noise. For example, a correlation between the two signals can be calculated in order to com pare them. If they are highly correlated, then it is likely that the have been measured on the same body.

The proposed concept is summarized by the flowchart 300 of Fig. 3.

The illustrated example includes measuring 310, at a first body portion (here, the user’s fin ger), a first signal 315 indicative of a first biometric identifier (here, the user’s heart rate). Further, a second signal 325 indicative of the same first biometric identifier is measured 320 at a second different body portion (here, the user’s wrist). In act 330 it is detected whether the first and second signals have been measured on the same body based on a comparison 335 of the measured first and second signals 315, 325. If the difference is small then it can be decided that they stem from the same body. If the difference is large, it is likely that the signals have not been measured at the same body. In the latter case, the process 300 may terminate or a warning signal may be issued.

The proposed concept can optionally also be used for authenticating a user. For this pur pose, an optional third sensor 160 may be foreseen which is configured to measure, at the same body portion as the first sensor 110, a third signal 165 indicative of a different second biometric identifier. In the illustrated example, the third sensor 160 is a fingerprint scanner collocated with or embedded in the first heart rate sensor 110 and configured to measure the fingerprint pattern of the user. The signal processor 150 can then be configured to authenti cate the user, if

a) the measured third signal 165 (e.g., measured fingerprint pattern) matches a stored signal (e.g., stored fingerprint pattern of the user), and

b) the difference between the first and the second signal 115, 145 indicating the user’s heart rate is below the predefined threshold.

Thus, a) and b) may have to be fulfilled at the same time in order to authenticate the user. Preferably, all the measurements of the signals 115, 145, and 165 are performed substantial ly at the same time, e.g., within a few seconds. In this way it can be ensured that the user who is wearing the wrist-wearable device 100 is the same that was authenticated with the fingerprint scanner 160. Thus, an increased level of protection from misuse or malicious intrusion can be provided.

Although, Figs. 1 and 2 depict an example device 100 where the biometric sensors 110, 140, and 160 are all integrated into one common device, the skilled person having benefit from the present disclosure will appreciate that sensors 110 and 160 could also be implemented remotely from sensor 140 in other embodiments and device 100 could merely include wire less or wired interfaces for the respective signals 115, 165.

In some example implementations, the second heart rate sensor 140 in the wearable device 100 can be configured to frequently or periodically measure the second signal 145 indicative of the user’s heart rate, for example, with a predefined measurement frequency. In this way, the user can be kept authenticated as long as the second heart rate sensor 140 frequently measures the second signal. Thus, as long as the user is not removing the wearable 100 from the wrist, the heart rate can be acquired continuously and compared to previous values. If the measured heart rate is stable and does not change abruptly (e.g., not more than a reason able deviation), the user can remain authenticated. If abrupt changes in the heart rate are detected it could mean that the sensor 140 was not in contact with the skin of the user during whole time. Therefore the user may be asked to authenticate again.

Additionally or alternatively, the first signal 115 from the first heart rate sensor 110 co- located with the fingerprint sensor 160 could be used as liveness detection for fingerprint biometrics. This might prevent an attacker to use a fake finger for the fingerprint scanner. If there is no pulse measured at the finger, the authentication process may be terminated im mediately.

The embodiments described with regard to the figures allow for recognizing a user based on blood volume pulse. They relate to an anti- spoof technique for fingerprint biometrics based on blood volume pulse. The example system comprises a fingerprint scanner 160 which includes a pulse sensor 110, and a second sensor 140 placed in the back part of a wristband. Thus, the finger print scanner 110, 160 also measures the blood volume pulse in the finger tip used to authenticate and the second sensor 140 measures the blood volume pulse under the skin. This can be used to ensure that the same person is wearing the wristband while his/her fingerprints are scanned. In this way it can be ensured that the user who is wearing the wristband is the same that was authenticated with the fingerprint scanner. Besides ensur ing continuous authentication, embodiments could be used for liveness detection which could provide an added value to fingerprint scanners.

The skilled person having benefit from the present disclosure will appreciate that the de scribed examples can be well translated to or combined with other biometric identifiers and sensors. Thus, apart from the described combination of fingerprint pattern and heart rate, any combination of any adequate first and second biometric identifiers is conceivable.

The following examples pertain to further embodiments.

(1) A method of signal detection. The method comprises measuring, at a first body por tion, a first signal indicative of a first biometric identifier, measuring, at a different second body portion, a second signal indicative of the first biometric identifier, and detecting whether the first and second signal are measured on the same body based on a comparison (335) of the measured first and second signals.

(2) The method according to (1), wherein measuring the first signal and/or the second signal comprises measuring a blood flow of the user.

(3) The method according to (1) or (2), wherein the first biometric identifier is the heart rate of the user.

(4) The method according to one of (1) to (3), further comprising measuring, at the first body portion, a third signal indicative of a second biometric identifier, and authenti cating the user, if the third signal matches a stored signal and if the difference between the first and the second signal is below the predefined threshold.

(5) The method according to (4), wherein measuring the third signal comprises measuring a fingerprint pattern of the user.

(6) The method according to any one of (1) to (5), wherein the second signal is measured frequently via a user-wearable sensor device.

(7) The method according to (6), further comprising, upon authenticating the user, keep ing the user authenticated as long as the user-wearable sensor device frequently measures the second signal.

(8) The method according to of any one of (1) to (7)„ wherein the first signal is measured at a finger.

(9) The method according to any one of (1) to (8), wherein the second signal is measured at a wrist.

(10) A device for signal detection. The device comprises at least one signal interface con figured to receive a first signal indicative of a first biometric identifier measured at a first body portion and to receive a second signal indicative of the first biometric iden tifier measured at a different second body portion, and a processor configured to de- tect whether the first and second signal have been measured on the same body based on a comparison of the first and the second signal.

(11) The device according to (10), wherein at least one signal interface is further config ured to receive a third signal indicative of a second biometric identifier measured at the first body portion, wherein the processor is configured to authenticate the user, if the third signal matches a stored signal and if a difference between the first and the second signal is below a predefined threshold.

(12) The device according to (11), comprising a second sensor configured to frequently measure, at the second body portion, the second signal, wherein the processor is con figured to detect whether the user is wearing the device based on the second signal.

(13) The device according to (12), further comprising a first sensor configured to measure, at the first body portion, the first signal indicative of the first biometric identifier, and a third sensor configured to measure, at the first body portion, the third signal indica tive of the second biometric identifier.

(14) The device according to any one of (11) to (13), wherein the third signal is indicative of a fingerprint pattern as the biometric identifier.

(15) The device according to any one of (10) to (14), wherein the first and the second sig nals are indicative of a heart rate as the first biometric identifier.

The aspects and features mentioned and described together with one or more of the previ ously detailed examples and figures, may as well be combined with one or more of the other examples in order to replace a like feature of the other example or in order to additionally introduce the feature to the other example.

Examples may further be or relate to a computer program having a program code for per forming one or more of the above methods, when the computer program is executed on a computer or processor. Steps, operations or processes of various above-described methods may be performed by programmed computers or processors. Examples may also cover pro gram storage devices such as digital data storage media, which are machine, processor or computer readable and encode machine-executable, processor-executable or computer- executable programs of instructions. The instructions perform or cause performing some or all of the acts of the above-described methods. The program storage devices may comprise or be, for instance, digital memories, magnetic storage media such as magnetic disks and magnetic tapes, hard drives, or optically readable digital data storage media. Further exam ples may also cover computers, processors or control units programmed to perform the acts of the above-described methods or (field) programmable logic arrays ((F)PLAs) or (field) programmable gate arrays ((F)PGAs), programmed to perform the acts of the above- described methods.

The description and drawings merely illustrate the principles of the disclosure. Furthermore, all examples recited herein are principally intended expressly to be only for pedagogical purposes to aid the reader in understanding the principles of the disclosure and the concepts contributed by the inventor(s) to furthering the art. All statements herein reciting principles, aspects, and examples of the disclosure, as well as specific examples thereof, are intended to encompass equivalents thereof.

A functional block denoted as“means for ...” performing a certain function may refer to a circuit that is configured to perform a certain function. Hence, a“means for s.th.” may be implemented as a“means configured to or suited for s.th.”, such as a device or a circuit con figured to or suited for the respective task.

Functions of various elements shown in the figures, including any functional blocks labeled as“means”,“means for providing a signal”,“means for generating a signal.”, etc., may be implemented in the form of dedicated hardware, such as“a signal provider”,“a signal pro cessing unit”,“a processor”,“a controller”, etc. as well as hardware capable of executing software in association with appropriate software. When provided by a processor, the func tions may be provided by a single dedicated processor, by a single shared processor, or by a plurality of individual processors, some of which or all of which may be shared. However, the term“processor” or“controller” is by far not limited to hardware exclusively capable of executing software, but may include digital signal processor (DSP) hardware, network pro cessor, application specific integrated circuit (ASIC), field programmable gate array (FPGA), read only memory (ROM) for storing software, random access memory (RAM), and non-volatile storage. Other hardware, conventional and/or custom, may also be includ- ed.

A block diagram may, for instance, illustrate a high-level circuit diagram implementing the principles of the disclosure. Similarly, a flow chart, a flow diagram, a state transition dia gram, a pseudo code, and the like may represent various processes, operations or steps, which may, for instance, be substantially represented in computer readable medium and so executed by a computer or processor, whether or not such computer or processor is explicit ly shown. Methods disclosed in the specification or in the claims may be implemented by a device having means for performing each of the respective acts of these methods.

It is to be understood that the disclosure of multiple acts, processes, operations, steps or functions disclosed in the specification or claims may not be construed as to be within the specific order, unless explicitly or implicitly stated otherwise, for instance for technical rea sons. Therefore, the disclosure of multiple acts or functions will not limit these to a particu lar order unless such acts or functions are not interchangeable for technical reasons. Fur thermore, in some examples a single act, function, process, operation or step may include or may be broken into multiple sub-acts, -functions, -processes, -operations or -steps, respec tively. Such sub acts may be included and part of the disclosure of this single act unless ex plicitly excluded.

Furthermore, the following claims are hereby incorporated into the detailed description, where each claim may stand on its own as a separate example. While each claim may stand on its own as a separate example, it is to be noted that - although a dependent claim may refer in the claims to a specific combination with one or more other claims - other examples may also include a combination of the dependent claim with the subject matter of each other dependent or independent claim. Such combinations are explicitly proposed herein unless it is stated that a specific combination is not intended. Furthermore, it is intended to include also features of a claim to any other independent claim even if this claim is not directly made dependent to the independent claim.