Patent Description:
Analysis of biological samples can provide useful information about the biological sample. The information that is obtained can be used for controlling an electronic device, perform diagnosis, health monitoring or any other suitable purpose.

<CIT> (D1) relates to a method and a device for creating digital copies of the ionic-electric dynamics of cells or cell compartments, such as organisms, or an at least partly identifying dataset that allows sorting decisions in vitro and in vivo. According to D1, an object under test, for example cells, cell aggregates or whole organisms becomes stimulated by a physical or chemical stimulus whose dynamic characteristics can be controlled. A control unit analyzes the measurements and generates, based on their results, subsequent stimuli with well-defined characteristics.

Examples of the disclosure relate to systems and methods for identifying characteristics of biological samples. The identified characteristics can be used for human-machine interactive purposes, health monitoring purposes, to provide control signals to electronic devices or computer programs, for diagnostic purposes or for any other suitable use.

In examples of the disclosure a plurality of electrical input signals can be provided to a biological sample so as to provide a plurality of corresponding electrical output signals. As the electrical output electrical signals have passed through the biological sample, the electrical output signals comprise of information about the properties of the biological sample. In examples of the disclosure, the electrical input signal can be controlled so that the electrical output signals comprise of general features and sub-features that enable characteristics of the biological sample to be identified. The use of these general features and sub-features can enable the characteristics to be identified without creating a reconstruction of the biological sample.

<FIG> schematically shows an example apparatus <NUM> for analysing a biological sample <NUM>. The apparatus <NUM> could be used for electrical impedance tomography or other types of analysis of biological samples.

The biological sample <NUM> can comprise an in-vivo sample. The biological sample <NUM> can comprise any biological cellular matter. In some examples, the biological sample <NUM> could comprise a part of a user's body or any other suitable biological sample <NUM>.

For instance, in some examples the biological sample <NUM> could comprise part of a person's arm and the apparatus <NUM> could be configured to detect movement or other changes of the arm.

The apparatus <NUM> can be configured to enable one or more characteristics of the biological sample <NUM> to be identified. The characteristic could comprise an intrinsic property of the biological sample <NUM>. For example, the characteristics could comprise an indication about the types of structures or component within the biological sample <NUM>. In such cases the characteristics could comprise information about a type of cell or tissue within the biological sample <NUM>. The characteristics could comprise information relating to the position of such cells and tissues and/or the size, shape and/or conductivities of such cells and tissues or any other suitable information.

In some examples the characteristics could comprise changes within the biological sample <NUM>. For example, the characteristics could comprise movement of the biological sample <NUM> and/or parts of the biological sample <NUM>. In some examples the changes could comprise a change in size and/or shape and/or position of cells or tissues or other components within the biological sample <NUM>. Other types of characteristics could be used in other examples of the disclosure.

The apparatus <NUM> comprises means for providing an electrical input signal <NUM> to the biological sample <NUM>. The electrical input signal <NUM> can comprise any electrical signal that can stimulate the biological sample <NUM> so as to elicit one or more electrical properties of the biological sample <NUM>. The electrical input signal <NUM> can be configured so that it does not cause irreversible damage to the cells and other components within the biological sample <NUM> or does not kill the cells or other components within the biological sample <NUM>.

The electrical properties of the biological sample <NUM> that are elicited can be any properties that can be measured or detected by using the plurality of electrical input signals <NUM>. The electrical properties that are elicited could comprise any one or more of resistance, capacitance, impedance, dielectric, phase or any other suitable property. The electrical properties of the biological sample <NUM> that are elicited could comprise properties of cells/tissues, or parts of cells and tissues, within the biological sample <NUM>.

The apparatus <NUM> can be configured to provide the electrical input signal <NUM> in programmed waveforms. The timing, intensity, frequency and any other suitable property of the electrical input signal <NUM> can be controlled through the apparatus <NUM>. The apparatus <NUM> can be configured to control the electrical input signal <NUM> so as to control one or more characteristics of the electrical output signals <NUM>. The apparatus <NUM> can be configured to control the electrical input signal <NUM> so that the electrical output signal <NUM> can be used to identify the characteristics of the biological sample <NUM>.

The apparatus <NUM> can comprise means for enabling the electrical input signals <NUM> to be provided to the biological sample <NUM>. The means can comprise one or more electrodes configured so that the electrical input signals <NUM> can be applied to the biological samples <NUM>. The electrodes can be configured to enable current from the electrodes to flow into the biological sample <NUM>.

The apparatus <NUM> also comprises means for receiving electrical output signals <NUM> from the biological sample <NUM>. The electrical output signals <NUM> correspond to the electrical input signals <NUM> in that they can be provided by the electrical input signals <NUM> passing through the biological sample <NUM>. As the electrical output signals <NUM> comprise signals that have passed through the biological sample <NUM>, the properties of the electrical output signals <NUM> are determined by the electrical properties of the biological sample <NUM>. This enables the electrical output signals <NUM> to provide information relating to the electrical properties of the cells within the biological sample <NUM> and so can provide information relating to one or more characteristics of the biological sample <NUM>.

The apparatus <NUM> also comprises means for enabling analysis of the electrical output signals <NUM>. In some examples the electrical output signals <NUM> can be analysed to determine one or more general features and one or more sub-features within the plurality of electrical output signals <NUM>. The one or more general features and one or more sub-features can enable one or more characteristics of the biological sample <NUM> to be identified. In some examples the general features or sub-features can be analysed by comparing them to reference signals. This can enable particular types of characteristics to be identified and/or monitored.

<FIG> schematically shows another example apparatus <NUM> and biological sample <NUM>. In this example the biological sample <NUM> comprises a part of a user's body.

In the example shown in <FIG> the example apparatus <NUM> comprises means <NUM> for providing an electrical input signal <NUM> to the biological sample <NUM> and means <NUM> for receiving an electrical output signal <NUM> from the biological sample <NUM>. The apparatus <NUM> could also comprise means for analysing electrical output signals <NUM> however this is not shown in <FIG>.

The means <NUM> providing an electrical input signal <NUM> to the biological sample <NUM> can comprise two or more electrodes <NUM>. The electrodes <NUM> can be positioned on the biological sample <NUM> so as to enable current from the electrodes <NUM> to flow from a first electrode <NUM> and through the biological sample <NUM> to the electrodes <NUM>. In the example of <FIG> the electrodes <NUM> are positioned on the skin of the user.

The apparatus <NUM> can be configured to enable parameters of the electrical input signal <NUM> to be adjusted as appropriate. The parameters that could be adjusted could comprise current amplitudes, voltage amplitudes, waveform, frequency or any other suitable parameter.

The control of the electrical input signal <NUM> can enable control of the interactions of the electrical input signal <NUM> with electrical properties within the biological sample <NUM>. This can then control the properties of the electrical output signals <NUM> obtained by the apparatus <NUM> from the biological sample <NUM>. The electrical input signal <NUM> can be adjusted to control general features and sub-features within the electrical output signals <NUM>. The electrical input signal <NUM> can be adjusted to control the size, shape, position and other suitable properties of the general features and sub-features within the electrical output signals <NUM>.

The means for providing the electrical input signal <NUM> to the biological sample <NUM> can be configured to enable the electrical input signal <NUM> to be provided to different parts of the biological sample <NUM> at different times. For example, the means for providing the electrical input signal <NUM> to the biological sample <NUM> could comprise a plurality of pairs of electrodes <NUM>. The plurality of pairs of electrodes <NUM> could be arranged in different positions on the biological sample <NUM>. The different pairs of the electrodes <NUM> could then be configured to provide the electrical input signal <NUM> to different parts of the biological sample <NUM> at different times.

The example apparatus <NUM> also comprises means <NUM> for receiving electrical output signals <NUM> from the biological sample <NUM>. In this example the means <NUM> comprises a plurality of electrodes <NUM> that can be positioned on the biological sample <NUM>. The electrodes <NUM> can be positioned on the biological sample <NUM> so as to enable an electrical output signal <NUM> to be received at one or more respective electrodes <NUM>. The electrodes <NUM> can be arranged so that the received electrical output signal <NUM> flows through a part of the biological sample <NUM> that interacted with the electrical input signal <NUM>.

In some examples the means <NUM> for providing a plurality of electrical input signals <NUM> and means for receiving a plurality of electrical output signals <NUM> could be configured to enable the plurality of electrical output signals <NUM> to be detected from different parts of the biological sample <NUM> at different times. For example, the means <NUM> for providing the plurality of electrical input signals <NUM> and the means <NUM> for receiving a plurality of electrical output signals <NUM> could comprise a plurality of pairs of electrodes <NUM>, <NUM>. The plurality of pairs of electrodes <NUM>, 207could be provided in different positions on the biological sample <NUM>. The different pairs of the electrodes <NUM>, <NUM> could then be configured to provide a plurality of electrical input signals <NUM> to, and receive a plurality of electrical output signals <NUM> from, different parts of the biological sample <NUM> at different times.

In some examples, an electrode <NUM>, <NUM> can form a stimulation pair with any other electrode <NUM>, <NUM> for delivering electrical input signal to the biological sample <NUM>, and all remaining electrodes <NUM>, <NUM> can form pairs of any combination to collect electrical output signals <NUM>.

The use of the different electrical input signals <NUM> at different parts of the biological sample <NUM> can enable characteristics of the biological sample <NUM> to be tracked both in time and in space. This can enable characteristics of different parts of the biological sample <NUM> to be identified. This can also enable changes of the characteristics to be identified. This can be used to detect and/or monitor movement of the biological sample <NUM> and/or other types of changes.

<FIG> also shows a section of a biological sample <NUM>. In this example the biological sample <NUM> comprises a part of a person. The biological sample <NUM> comprises a user's skin. In the example of <FIG> the electrodes <NUM>, <NUM> of the apparatus <NUM> are positioned on the skin.

As shown in <FIG> the biological sample <NUM> comprises a plurality of different types of tissue <NUM>. The different types of tissue can have different electrical responses to the electrical input signals <NUM>. The different tissues can also comprise different structures within them. For example, the different tissues in the biological sample <NUM> shown in <FIG> can comprise capillaries, arterioles, arteries and other structures. Other types of structures could be provided within the biological sample <NUM> in other examples of the disclosure. For instance, the biological sample could comprise bones or muscles or any other types of structures or other components.

Characteristics of these tissues <NUM> such as their thickness or shape or the presence of other components within the tissues <NUM> can be detected using the apparatus <NUM>. In some examples the apparatus <NUM> can also be configured to detect movement or other changes in these tissues <NUM>.

<FIG> shows a section of a biological sample <NUM> in more detail. This shows some of the cells <NUM> within the biological sample <NUM>. <FIG> shows that an electrical input signal <NUM> can be provided so that it passes through the cells <NUM> or so that it passes around the cells <NUM>. Whether the electrical input signal <NUM> passes through the cells <NUM> or passes around the cells <NUM> can determine how the electrical input signal <NUM> interacts with the electrical properties of the biological sample <NUM>. This can affect the values in the electrical output signals <NUM> that are detected by the apparatus <NUM>. For example, this can affect any general features and the sub-features within the electrical output signals <NUM>. This could change the amplitude, shape or other properties of the general features and the sub-features within the electrical output signals <NUM>. The way in which the general features and the sub-features within the electrical output signals <NUM> are affected can be used to identify one or more characteristics of the biological sample <NUM>.

<FIG> shows a method that can be implemented using an apparatus <NUM> as shown in <FIG> and <FIG>. The method enables information to be obtained from a biological sample <NUM> such that the information can be used to identify characteristics of the biological sample <NUM>.

The method comprises, at block <NUM>, providing an electrical input signal <NUM> to a biological sample <NUM>. The electrical input signal <NUM> interacts with the biological sample <NUM> so as to elicit one or more electrical properties of the biological sample <NUM>. The electrical properties of the biological sample <NUM> that are elicited could comprise any one or more of electrical responses such as resistance, capacitance, impedance, dielectric, phase or any other suitable property.

The electrical input signals <NUM> can be provided using any suitable means. In some examples the electrical input signals <NUM> can be provided by two or more electrodes <NUM> positioned on the biological sample <NUM>. The two or more electrodes <NUM> can be positioned in any suitable locations on the biological sample <NUM>. In some examples the electrodes <NUM> can be positioned adjacent to each other. In some examples the electrodes <NUM> can be positioned on different sides of the biological sample <NUM> to each other.

In some examples the electrodes <NUM> can be configured to provide a plurality of pairs of electrodes <NUM>. The plurality of different pairs can comprise any suitable combinations of electrodes <NUM> within the available set of electrodes <NUM>. The plurality of different pairs of electrodes <NUM> can be configured so that the electrical input signals <NUM> can be provided by different pairs of the electrodes <NUM> at different times. This can enable the electrical input signals <NUM> to be provided to different parts of the biological sample <NUM> at different times.

At block <NUM> the method also comprises receiving a plurality of electrical output signals <NUM> from the biological sample <NUM>. The electrical output signals <NUM> correspond to the electrical input signals <NUM>. The electrical output signals <NUM> correspond to the electrical input signals <NUM> in that they are provided by the electrical input signals <NUM> passing through the biological sample <NUM>. As the received electrical output signals <NUM> have passed through the biological sample <NUM> the values of the electrical output signals <NUM> are determined by the electrical properties of the biological sample <NUM>.

The electrical output signals <NUM> can be received using any suitable means. In some examples the electrical output signals <NUM> can be received by one or more electrodes <NUM> positioned on the biological sample <NUM>. The one or more electrodes <NUM> can be positioned in any suitable locations on the biological sample <NUM>. The electrodes <NUM> that are used to receive the electrical output signals <NUM> can be positioned so that the electrical input signal <NUM> has passed through a part of the biological sample <NUM> before it is received by the electrode <NUM>.

The method also comprises, at block <NUM>, controlling the electrical input signals <NUM> so that the plurality of electrical output signals <NUM> from the biological sample <NUM> comprise one or more general features and one or more sub-features. The values of the electrical output signals <NUM> can be determined by the electrical properties of the biological sample <NUM> and how these interact with the electrical input signals <NUM>. Therefore, by controlling the electrical input signal <NUM> the values of the electrical output signals <NUM> can be tuned so as to provide one or more general features and one or more sub-features in the electrical output signals <NUM>.

The one or more general features and the one or more sub-features enable one or more characteristics of the biological sample <NUM> to be identified. The one or more general features and the one or more sub-features can comprise measurement points within one or more of the electrical output signals <NUM>.

The general features and the sub-features in the electrical output signals <NUM> can comprise measurement points that enable different types of biological samples <NUM> to be differentiated from each other. For example, a first pattern of general features and the sub-features can indicate that the biological sample <NUM> is a first type of sample and a second pattern of general features and sub-features can indicate that the biological sample <NUM> is a second type of sample.

The sub-features can comprise features that are more subtle than the general features. For instance, in some examples the sub-features can comprise features that can be identified by comparison with reference signals whereas the general features could comprise features that can be identified without comparison to reference signals.

In some examples the general features can comprise one or more global extrema within one or more of the electrical output signals <NUM> and the sub-features can comprise local extrema within the one or more electrical output signals <NUM>. For instance, the general features could comprise global maxima or minima within the electrical output signals <NUM> and the sub-features could comprise local maxima or minima. The local maxima or minima could have a smaller amplitude than the global maxima or minima.

In some examples the one or more general features can comprise a most significant feature within the electrical output signals <NUM> and the one or more sub-features can comprise less significant features within the electrical output signals <NUM>. The sub-features can be less significant in that they are more hidden and less obvious or visible within the electrical output signals <NUM>. The sub-features could have smaller amplitudes or be provided closer to other sub-features within the output signal.

Different electrical output signals <NUM> can comprise different general features and sub-features. For instance, in some examples, the biological sample <NUM> can be probed in a plurality of different directions by applying the electrical input signal <NUM> and the electrical output signal <NUM> through different pairs of electrodes in different directions across the biological sample <NUM>. The different electrical output signals <NUM> could then comprise information obtained from the different directions.

In some examples changes of the biological sample <NUM> could also enable the biological sample <NUM> to be probed in different directions. The changes of the biological sample <NUM> could comprise movement of the biological sample <NUM>, movement of parts of the biological sample <NUM> or any other suitable changes of the biological sample <NUM>.

The measurement points that provide the general features and sub-features can be obtained by probing the biological sample <NUM> using one or more different temporal patterns. The different temporal patterns can comprise different time points, intervals, cycles, periodicities or any other parameters for the electrical input signals <NUM>.

The controlling of the electrical input signals <NUM> can comprise controlling one or more parameters so as to create and tune the one or more general features and one or more sub-features in the electrical output signal <NUM>. The parameters of the electrical input signal <NUM> that can be controlled can comprise current amplitudes, voltage amplitudes, waveform, frequency or any other suitable parameter.

In some examples the input electrical input signal <NUM> can be controlled to enable different general features and/or sub-features to be provided in the electrical output signals <NUM>. For instance, changing one or more parameters in the input electrical input signal <NUM> can cause a corresponding change in the general features and/or sub-features in the output signals <NUM>. These changes in the general features and/or sub-features can be used to identify characteristics of the biological sample <NUM>.

In some examples the characteristics of the biological sample <NUM> can be identified by correlating the one or more general features and one or more sub-features in the electrical output signals <NUM> from the biological sample <NUM> with one or more reference signals. The reference signals could be obtained through in-vivo and in-vitro measurements or from simulations or by any other suitable means. If there is a sufficient level of correlation with a reference signal, then this can provide an identification of one or more characteristics of the biological sample <NUM>.

In some examples the method can comprise comparing at least some of the features in the electrical output signals <NUM> with experimentally determined features to enable changes within the biological sample <NUM> to be identified.

Some examples of characteristics of the biological sample <NUM> that can be identified can comprise movement of the biological sample <NUM>, position of the biological sample <NUM>, size of the biological sample <NUM>, shape of the biological sample <NUM>, conductivity of the biological sample <NUM>. In some examples the characteristics can be characteristics of part of the biological sample <NUM>. For example, the characteristics could be the size and/or shape of a type of tissue within the biological sample <NUM> or of any other suitable part of the biological sample <NUM>. Other characteristics could be used in other examples of the disclosure.

In some examples the apparatus <NUM> can be configured to perform additional steps in order to enable the characteristics of the biological sample <NUM> to be identified. For instance, the apparatus <NUM> can be configured to selectively combine one or more general features and one or more sub-features from one or more electrical output signals <NUM> and use that combination to identify one or more characteristics of the biological sample <NUM>. In some examples the electrical output signal <NUM> can be processed to parse the general features and sub-features into different proportions or ratios. The processing that is performed can ensure that there is at least one feature that can be used to identify characteristics of the biological sample <NUM>.

The use of the general features and sub-features within the electrical output signals <NUM> can enable the characteristics of the biological sample <NUM> to be identified without generating a reconstruction of the biological sample <NUM>. For instance, there would be no need to generate a reconstruction such as an image or other model of the biological sample <NUM> in order to enable the characteristics to be identified. This can enable the characteristics to be identified more quickly and accurately and can reduce the processing requirements of the apparatus <NUM>. In some examples this can enable the identification of the characteristics to be used as an input for an electronic device or computer program. For example, it could enable the electrical output signals <NUM>, or data obtained from the electrical output signals <NUM>, to be used to provide a control input to a device or computer program or any other suitable entity.

<FIG> schematically shows an implementation of examples of the disclosure. In this example the apparatus <NUM> can be configured to detect movement of the biological sample <NUM>. For instance, the biological sample <NUM> could comprise part of an arm of a user and the apparatus <NUM> could be configured to detect movements of the user's muscles when the user makes a gesture using their arm. The gesture could be a two-finger pinch gesture comprising a user bringing two of their fingers together or any other suitable type of gesture.

<FIG> shows an apparatus <NUM> that is configured to provide a plurality of electrical input signals <NUM> to a biological sample <NUM>.

The parameters of the electrical input signals <NUM> can be controlled so as to tune electrical output signals <NUM> to comprise general features and sub-features that can be used to identify characteristics of the biological sample <NUM>.

The parameters of the electrical input signals <NUM> that are controlled can comprise any suitable parameters and/or combination of parameters. In some examples the parameters could comprise the drive pattern for the electrical input signals <NUM>. The drive pattern could comprise the sequence in which the available electrodes <NUM> are used to provide the electrical input signals <NUM>. In some examples the parameters could comprise the frequency of the electrical input signals <NUM>. In some examples the parameters could comprise the arrangement of the electrodes <NUM> that are used to provide the electrical input signals <NUM>. For example, it could comprise the positions of the electrodes <NUM> on the biological sample <NUM> and/or the positions of the electrodes <NUM> relative to each other. Other parameters could be used in other examples of the disclosure.

The electrical input signals <NUM> are provided to the biological sample <NUM>. In this example the biological sample <NUM> comprises three muscles <NUM> that can move as the user makes the gesture. For example, the muscles 401A-C can expand or contract as the user moves their fingers. This can alter the shape of the muscles <NUM> within the biological sample <NUM>. The muscles <NUM> are shown schematically in <FIG>.

The electrical input signals <NUM> can change the electrical properties of the muscles <NUM> and/or the parts of the biological sample <NUM> around the muscles <NUM>. When an electrical input signal <NUM> is provided to the biological sample <NUM> this will pass through the muscles <NUM> to provide the electrical output signals <NUM>. The modification of the electrical properties of the muscles <NUM> therefore determines the values of the electrical output signals <NUM>.

<FIG> also shows a plurality of plots <NUM> indicative of the electrical output signals <NUM>. The plots <NUM> shown in <FIG> show values of different parameters of the electrical output signals <NUM>. In the example of <FIG> the plots show values of impedance, phase, voltage and quadrature. The vertical axis of the plots indicates these values. Other parameters could be used in other examples of the disclosure.

The horizontal axis of these plots <NUM> corresponds to the different observations or measurements made by the physical electrodes <NUM>, <NUM>. The values are obtained for signals obtained between different pairs of electrodes <NUM>, <NUM>. The different pairs of electrodes <NUM>, <NUM> can correspond to different parts of the biological sample <NUM> and/or to different probing directions of the biological sample <NUM>. In this example, each of the plots <NUM> comprise thirty-two different measurements along the horizontal axis. These measurements are obtained using different pairs of electrodes <NUM>, <NUM> to provide electrical input signals <NUM> and electrical output signals <NUM>. Other numbers of measurements could be used in other examples of the disclosure.

The plots <NUM> comprise general features <NUM> and sub-features <NUM>. The general features <NUM> comprise measurement points that can be easily identified within the plots <NUM>. In this example the general features <NUM> can comprise the global maxima of one or more parameters within the electrical output signals <NUM>. The sub-features <NUM> can comprise measurement points that have a smaller amplitude compared to the general features. The sub-features <NUM> could comprise a sequence of measurement points that have a predefined pattern. The sub-features <NUM> could comprise local maxima or any other suitable type of measurement points.

In the example of <FIG> each of the muscles <NUM> provide different general features <NUM> and sub-features <NUM>. These general features <NUM> and sub-features <NUM> can provide an indication of the shape or position of each of the muscles <NUM>. The combination of these different general features <NUM> and sub-features <NUM> can therefore be used to identify patterns of movement of the muscles <NUM> and so can identify when a gesture has been performed.

In the example of <FIG> the first set comprises a general feature 405A and sub-feature 407A. The first set can correspond to a first muscle 401A in that the amplitude and position of these features 405A, 407A are determined by the characteristics of the first muscle 401A. The second set comprises two sub-features 407B. The second set can correspond to a second muscle 401B in that the amplitude and position of these features 407B are determined by the characteristics of the second muscle 401B. The third set comprises two general features 405C. The third set can correspond to a third muscle 401C in that the amplitude and position of these features 405C are determined by the characteristics of the third muscle 401C.

In order to identify whether or not a gesture has been determined the values of the parameters within the electrical output signals <NUM> can be compared to one or more reference signals. In some examples only a section of the electrical output signals <NUM> might be compared to the reference signals. For instance, only the sections of the electrical output signals <NUM> in which the general features <NUM> and/or the sub-features <NUM> are expected to be might be compared.

The reference signals used for the comparison can be obtained from experimental results, from simulations or by any other suitable means. The comparison with the reference signals can provide an indication as to whether or not a gesture has been performed. For instance, the electrical output signals <NUM>, or parts of the electrical output signals <NUM> can be correlated with the reference signals and if the correlation is within a threshold amount it can be determined that the general features <NUM> and sub-features <NUM> are indicative of the gesture being performed.

<FIG> shows how examples of the disclosure can be used to detect changes of a biological sample <NUM>.

<FIG> schematically shows an object <NUM> within a circular receptacle <NUM>. The object comprises a wooden cylinder <NUM>. The wooden cylinder <NUM> can move around within the circular receptacle <NUM>. The wooden cylinder <NUM> and circular receptacle <NUM> provide a simplified model of biological sample <NUM> and are used in this example to show how different electrical output signals <NUM> are provided when there are changes within the biological sample <NUM>. In this example the changes within a biological sample <NUM> are represented by changes in position of the wooden cylinder <NUM>.

In order to obtain the electrical output signal <NUM> a plurality of electrodes is positioned around the edge of the circular receptacle <NUM>. The electrodes can be configured to enable an electrical input signal <NUM> to be input to the circular receptacle <NUM> and pass through the circular receptacle <NUM> and the wooden cylinder <NUM> to provide an electrical output signal <NUM>.

In this example eight electrodes are distributed around the edge of the circular receptacle <NUM>. The electrodes are provided at regular intervals around the edge of the circular receptacle <NUM>. The circular receptacle <NUM> can be probed at different directions by using different pairs of the electrodes for the electrical input signal <NUM> and the electrical output signals <NUM>. Different permutations of the available electrodes can be used to probe the circular receptacle <NUM> at different directions and at different times.

<FIG> shows plots 403A -403D of different electrical output signals <NUM> that could be obtained for different configurations of the wooden cylinder <NUM> and circular receptacle <NUM>. The plots correspond to experimental data that was obtained using the wooden cylinder <NUM> and circular receptacle <NUM>.

The plots 403A- 403D shown in <FIG> show values of impedance of the electrical output signals <NUM>. In other examples, the 403A- 403D could show values of other electrical properties such as phase angle, quadrature and or any other suitable parameter. In this example, the vertical axis of the plots 403A- 403D indicates these impedances. The horizontal axis of these plots 403A- 403D correspond to the different permutations of pairs of electrodes that are used. Each of the plots 403A-403D comprise thirty-two different measurements along the horizontal axis. These measurements are obtained using different pairs of electrodes to provide electrical input signals <NUM> and electrical output signals <NUM>.

In the first plot 403A the wooden cylinder <NUM> was positioned in a lower right position within the circular receptacle <NUM>. In the second plot 403B the wooden cylinder <NUM> was positioned in an upper position within the circular receptacle <NUM>. In the third plot 403C the wooden cylinder <NUM> was positioned in a lower left position within the circular receptacle <NUM>. In the fourth plot 403D the wooden cylinder <NUM> was positioned in a central position within the circular receptacle <NUM>.

Each of the plots 403A, 403B, 403C, 403D comprise different measure points. The different measurement points provide different general features and sub-features. These general features and sub-features can therefore be used to identify characteristics such as the position or movement of the wooden cylinder <NUM> within the circular receptacle <NUM>.

Therefore, these experimental results show how different general features and sub-features within an electrical output signal <NUM> can be used to identify at least the position of an object. This could therefore be used to identify characteristics such as the position of components within a biological sample <NUM>.

The use of different directions to probe the circular receptacle <NUM> can enable small movements of the wooden cylinder <NUM> to be detected. The movements of the wooden cylinder <NUM> can cause a change in different parts of the electrical output signal <NUM> corresponding to measurements made between different electrodes. This causes a change in the general features and sub-features within the electrical output signal <NUM> that enables the movements to be identified.

<FIG> and <FIG> show example output signals. <FIG> shows a plurality of different plots 403A- 403I corresponding to electrical output signals <NUM> received at different times. These plots can be obtained from a wooden cylinder <NUM> moving around a circular receptacle <NUM> as shown in <FIG>.

The plots 403A- 403I shown in <FIG> show values of impedance of the electrical output signals <NUM>. The vertical axis of the plots indicates these impedances. The horizontal axis of these plots 403A- 403I corresponds to the different permutations of pairs of electrodes that are used. Each of the plots 403A-403I comprise thirty-two different measurements along the horizontal axis. These measurements are obtained using different pairs of electrodes to provide electrical input signals <NUM> and electrical output signals <NUM>.

<FIG> shows a comparison between two of the plots. In this example the comparison is made between the first plot 403A and the third pot 403C. The comparison could be made between any permutations comprising two or more of the plots.

To make the comparison a plurality of data points from the first plot 403A are compared to a plurality of data points from the second plot 403C. In this example only a subset of the available data points is compared. In other examples all of the available data points from the two plots 403A, 403C could be compared.

In the example of <FIG> the data points are compared from the fifteenth data point in each of the plots 403A, 403C. Other sections of the plots 403A, 403C could be used in other examples of the disclosure.

The section of the plots that are to be compared can be selected based on the information that is to be collected. For example, different parts of the plots 403A, 403C can correspond to different parts of the circular receptacle <NUM>. The area of the circular receptacle <NUM> in which the wooden cylinder <NUM> is moving through could provide the most useful information as this could be the area that is changing.

The comparisons enable the differences between the two plots to be compared as indicated by the arrows <NUM>. These differences, rather than the original plots 403A, 403B can be used to identify the features and sub-features in the electrical output signals <NUM>.

The examples show in <FIG> and <FIG> have been obtained using a wooden cylinder <NUM> moving around within a circular receptacle <NUM> however it is to be appreciated that the principles can be extended to biological samples <NUM>.

<FIG> show example output signals. <FIG> shows a first plot 701A and a second plot 701B. The first plot 701A is obtained using a wooden cylinder <NUM> within a circular receptacle <NUM> as shown in <FIG>. The second plot 701B is obtained by replacing the wooden cylinder <NUM> with a metal cylinder. As the wooden cylinder <NUM> and the metal cylinder have different electrical properties, they provide different electrical output signals <NUM>.

The plots 701A and 701B shown in <FIG> show values of impedance of the electrical output signals <NUM>. The vertical axis of the plots indicates these impedances. The horizontal axis of these plots 701A and 701B corresponds to the different permutations of pairs of electrodes that are used. Each of the plots 701A and 701B comprise thirty-two different measurements along the horizontal axis. These measurements are obtained using different pairs of electrodes to provide electrical input signals <NUM> and electrical output signals <NUM>. These plots clearly show different general features and sub-features due to the different electrical properties of the cylinders that have been used.

<FIG> shows a comparison between sections of the two plots 701A and 701B. To make the comparison a plurality of data points from the first plot 701A are compared to a plurality of data points from the second plot 701B. In this example only a subset of the available data points is compared. In other examples all of the available data points from the two plots 701A and 701B could be compared.

The comparisons enable the differences between the two plots 701A and 701B to be compared as indicated by the arrows <NUM>. These differences, rather than the original plots 701A and 701B can be used to identify the general features and sub-features in the electrical output signals <NUM>.

The arrows <NUM> show example comparisons between example parts of the 701A and 701B. Other parts of the plots 701A and 701B could be compared in other examples. The parts of the plots 701A and 701B that are to be compared can be determined through experiments. For instance, it can be identified that a first point indicates responses from an upper part of a muscle while a second point indicates responses from a lower part of a muscle. Comparing these two points can therefore give an indication of the contraction of that muscle.

The examples shown in <FIG> have been obtained using a wooden cylinder and metal cylinder <NUM> in a static position within a circular receptacle <NUM> however it is to be appreciated that the principles can be extended to biological samples <NUM>. For example, the electrical signals <NUM> can be used to change the electrical properties of the biological sample <NUM> or of a part of the biological sample <NUM>. This can provide different plots that can then be compared as shown in <FIG> so that the characteristics of the biological sample can be identified using the general features and the sub-features.

<FIG> shows another example plot <NUM> obtained from electrical output signals <NUM>. The plot <NUM> could be obtained from a biological sample <NUM> using methods and apparatus <NUM> as described herein.

In this example the biological sample <NUM> can be a complex sample comprising different types of tissues or other entities that can move or that have other properties that can change. For example, if the biological sample <NUM> comprises part of a user's arm, then different muscles within the arm can expand and contract as the user makes gestures or other movements.

The changes in the different components within the biological sample <NUM> can result in different patterns being identifiable within the output signals <NUM>. The plot in <FIG> shows three different patterns 803A. 803B and 803C. Each of these patterns 803A, 803B and 803C can correspond to different tissues or other components within the biological sample <NUM>.

The different patterns can comprise different general features <NUM> and sub-features <NUM>. The different general features and sub-features can enable the different characteristics of the biological sample <NUM> to be identified. In this example the different characteristics can comprise the different muscles and movement or other changes of these muscles.

In this example the first pattern 803A comprises a general feature 405A and a sub-feature 407A. The second pattern 803B comprises a general feature 405B and a sub-feature 407B. The third pattern 803C comprises two general features 405C. Other patterns comprising other arrangements of general features and sub-features <NUM> can be obtained in other examples of the disclosure.

The expected patterns for a given type of biological sample <NUM> and/or gesture made using a biological sample <NUM> could be determined from experimental data. For instance, a plurality of test biological samples <NUM> comprising known tissues could be used to make some predetermined gestures and the data could be collected to determine a reference output signal comprising expected general features <NUM> and sub-features <NUM> for a given type of biological sample <NUM> and/or gestures. When the apparatus <NUM> is being used the electrical output signals <NUM> obtained from the biological sample <NUM> can be compared to the reference signals to enable characteristics of the biological sample <NUM> to be identified.

<FIG> shows example plots 901A-901C obtained from electrical output signals <NUM>. These plots 901A-901C are obtained using a wooden cylinder <NUM> and a metal cylinder provided within a circular receptacle <NUM> as described above. These plots 901A-901C show that patterns resulting from the two different types of cylinder can be identified in the electrical output signals <NUM>.

The first plot 901A is obtained when only a wooden cylinder <NUM> was located within the circular receptacle <NUM>. This shows a pattern comprising general features and sub-features. In particular, this shows a cluster of sub-features at the left hand side of the plot 901A, a general feature comprising a minima in the centre of the plot 901A and a general feature comprising a maxima at the right hand edge of the plot 901A.

The second plot 901B is obtained when only a metal cylinder was located within the circular receptacle <NUM>. This shows a different pattern comprising different general features and sub-features. In particular this shows a plurality of sub-features around the middle of the plot 901B, and a general feature comprising a maxima positioned towards the right hand side of the plot 901B.

The third plot 901C is obtained when both a wooden cylinder <NUM> and a metal cylinder were located within the circular receptacle <NUM>. This third plot 901C shows the patterns from both the first plot 901A and the second plot 901B. The general features and the sub-features from both the first plot 901A and the second plot 901B can be identified in the third plot 901C. This indicates that two different types of cylinders were present. By comparing the general features and sub-features in the third plot 901C to the general features and the sub-features in the first plot 901A and the second plot 901B, the type of cylinders that were used, among other characteristics of the cylinders, can be identified.

This demonstrates that patterns corresponding to specific components can be identified within the electrical output signals <NUM>. The identification of these patterns can enable characteristics of complex biological samples <NUM> to be identified. This shows a validation experiment that shows that a correlation can be established between the general features and the sub-features in different electrical output signal signals <NUM>. When the examples of the disclosure are being used to monitor a biological sample <NUM> the plots obtained from the biological sample <NUM> can be compared to one or more reference signals.

<FIG> shows example plots 1001A-1001C obtained from electrical output signals. The example of <FIG> shows three different plots. Each of the plots 1001A-1001C comprise thirty-two different measurements obtained using different pairs of electrodes to provide an input signal <NUM> and an electrical output signal <NUM>.

The data in the different plots 1001A-1001C shown in <FIG> were obtained using a wooden cylinder <NUM> in a circular receptacle <NUM> as described previously. In this example the wooden cylinder was not moving and remained in the same position within the circular receptacle <NUM>. In this example the three different plots were obtained by using three different simulation conditions. For example, different parameters for the electrical input signals <NUM> could be used to obtain the three different plots 1001A-1001C.

In the particular example of <FIG> the electrical input signals <NUM> could be provided between two opposing electrodes to obtain a first plot 1001A and between electrodes that are offset diagonally to obtain the other plots 1001B and 1001C. This generates three different electrical output signals <NUM> comprising general features and sub-features that are unique to the sample object or type of object being sampled.

The plots shown in <FIG> are obtained from a model that is used to represent a biological sample <NUM>. This shows that the general features and sub-features of the electrical output signals <NUM> can be modified by controlling the parameters of the electrical input signals <NUM> and can therefore be used to identify characteristics of the biological sample <NUM>.

<FIG> schematically show different example of current injection and measurement pairings that can be used to obtain the different measurements.

This example shows eight different electrodes 1101A-<NUM> that could be positioned on a biological sample <NUM>. In this example, eight different electrodes 1101A-<NUM> are arranged around the circumference of a circle. The eight different electrodes 1101A-<NUM> are arranged at equal angular intervals around the circumference of a circle. Other arrangements for the electrodes 1101A-<NUM> can be used in other examples of the disclosure.

In this example the electrodes 1101A-<NUM> are in fixed positions. The electrodes 1101A-<NUM> in this example do not move relative to the biological sample <NUM>.

In this example the electrodes 1101A-<NUM> are configured so that they can be used for providing measurement signals, that is, the electrical input signals <NUM> and the electrical output signals <NUM>. The electrodes 1101A-<NUM> can be used to provide different signals at different times.

In these examples each of the electrodes 1101A-<NUM> can form a stimulation pair with any other electrode 1101A-<NUM> for delivering electrical input signals <NUM> to the biological sample <NUM>. The remaining electrodes 1101A-<NUM> can form pairs of any combination to collect electrical output signals <NUM>.

In these examples the dashed lines show the electrical input signals <NUM> and the solid lines show the electrical output signals <NUM>.

In <FIG> the electrical input signals <NUM> are provided from electrode 1101A to electrode 1101E. Electrical output signals <NUM> signals are received by the pairs of electrodes that are not used to provide the electrical input signals <NUM>. In the example of <FIG>, four sets of electrical output signals <NUM> are provided. These are provided between electrodes 1101B and 1101C, between electrodes 1101C and 1101D, between electrodes 1101F and <NUM>, and between electrodes <NUM> and <NUM>. This provides four data points for the plots as shown herein.

<FIG> show similar arrangements for the electrical input signals <NUM> and the electrical output signals <NUM>. However, by changing the electrodes that are used the biological sample <NUM> can be probed in different directions and/or the measurement signals can be obtained from different areas.

In <FIG> the electrical input signals <NUM> are provided from electrode 1101B to electrode 1101F. The electrical output signals <NUM> are received between electrodes 1101C and 1101D, between electrodes 1101D and 1101E, between electrodes <NUM> and <NUM>, and between electrodes <NUM> and 1101A.

In <FIG> the electrical input signals <NUM> are provided from electrode 1101C to electrode <NUM>. The electrical output signals <NUM> are received between electrodes 1101D and 1101E, between electrodes 1101E and 1101F, between electrodes <NUM> and 1101A, and between electrodes 1101A and 1101B.

In <FIG> the electrical input signals <NUM> are provided from electrode 1101D to electrode <NUM>. The electrical output signals <NUM> are received between electrodes 1101E and 1101F, between electrodes 1101F and <NUM>, between electrodes 1101A and 1101B, and between electrodes 1101B and 1101C.

In <FIG> the electrical input signals <NUM> are provided from electrode 1101E to electrode 1101A. The electrical output signals <NUM> are received between electrodes 1101F and <NUM>, between electrodes <NUM> and <NUM>, between electrodes 1101B and 1101C, and between electrodes 1101C and 1101D.

In <FIG> the electrical input signals <NUM> are provided from electrode 1101F to electrode 1101B. The electrical output signals <NUM> are received between electrodes <NUM> and <NUM>, between electrodes <NUM> and 1101A, between electrodes 1101C and 1101D, and between electrodes 1101D and 1101E.

In <FIG> the electrical input signals <NUM> are provided from electrode <NUM> to electrode 1101C. The electrical output signals <NUM> are provided between electrodes <NUM> and 1101A, between electrodes 1101A and 1101B, between electrodes 1101D and 1101E, and between electrodes 1101E and 1101F.

In <FIG> the electrical input signals <NUM> are provided from electrode <NUM> to electrode 1101D. The electrical output signals <NUM> are provided between electrodes 1101A and 1101B, between electrodes 1101B and 1101C, between electrodes 1101E and 1101F, and between electrodes 1101F and <NUM>.

Therefore in total this provides thirty-two data points for the plots as shown herein. This shows that a large number of data points can be obtained from just eight electrodes. Other numbers, arrangements, and/or configurations of electrodes could be used in other examples of the disclosure. If a larger number of electrodes are used then this could enable an even larger number of data points to be obtained. This can increase the resolution of the electrical output signal <NUM> that is obtained for identification of characteristics of biological samples <NUM>.

<FIG> shows example plots 1201A-1201F obtained from electrical output signals. The example of <FIG> shows six different plots. Each of the plots 1201A-1201F comprise thirty-two different measurements obtained using different pairs of electrodes such as the electrode pairs shown in <FIG>.

In this example the different plots are provided by movement of an object within a biological sample <NUM>. For example, a muscle could move within a biological sample <NUM>. The different plots 1201A-1201F can be obtained at different times as the parts of the biological sample <NUM> are moving. The different plots obtained at different times could be used to identify the movement of the muscle. The movement of the muscle could provide an indication of a type of gesture that is being performed.

In some examples electrical output signals <NUM> and/or the different plots obtained from the electrical output signals <NUM> can be combined so as to provide a multi-dimensional data set.

<FIG> shows example plots 1301A-1301D obtained from electrical output signals <NUM>. The plots 1301A-1301D can be compared and/or combined with each other to enable to provide multi-dimensional datasets from which general features and/or sub-features can be identified.

The combining and/or mixing of the different plots 1301A-1301D is possible because each of the points or measurements in 1301A-1301D is independent of the other points or measurements in 1301A-1301D. This can also enable different parts of the plots 1301A-1301D to be aligned with any other part of the other plots 1301A-1301D. For example, sections of a first plot can be combined and/or mixed with sections of another plot so as to enable general features and/or sub-features to be identified.

<FIG> shows a plurality of different plots. In this example four different plots 1301A-1301D are shown. The different plots 1301A-1301D are shown in some different combinations to show how they could be combined.

<FIG> shows a comparison of two plots 1301A and 1301D. The differences between them are indicated by the arrows. The differences between the two plots 1301A and 1301D provide an indication of a general feature and/or sub-features of the electrical output signals <NUM>. <FIG> shows a comparison between another two different plots 1301C and 1301B. The differences between these plots 1301C and 1301B can provide an indication of another general feature and/or sub-features. <FIG> shows a comparison between a further set of two different plots 1301D and 1301B. The differences between these plots 1301D and 1301B can provide an indication of a further general feature and/or sub-features.

Therefore, by combining and/or comparing different plots, different features and/or sub-features can be identified. This can enable more accurate identification of the characteristics of the biological sample <NUM> and/or could enable different types of biological sample to be identified.

<FIG> schematically illustrates a controller apparatus <NUM> according to examples of the disclosure. The controller apparatus <NUM> illustrated in <FIG> can be a chip or a chip-set. In some examples the controller apparatus <NUM> can be provided within a computer or other device that be configured to provide and receive signals.

In the example of <FIG> the controller apparatus <NUM> comprises a controller <NUM>. In the example of <FIG> the implementation of the controller <NUM> can be as controller circuitry. In some examples the controller <NUM> can be implemented in hardware alone, have certain aspects in software including firmware alone or can be a combination of hardware and software (including firmware).

As illustrated in <FIG> the controller <NUM> can be implemented using instructions that enable hardware functionality, for example, by using executable instructions of a computer program <NUM> in a general-purpose or special-purpose processor <NUM> that can be stored on a computer readable storage medium (disk, memory etc.) to be executed by such a processor <NUM>.

The processor <NUM> can also comprise an output interface via which data and/or commands are output by the processor <NUM> and an input interface via which data and/or commands are input to the processor <NUM>.

The memory <NUM> is configured to store a computer program <NUM> comprising computer program instructions (computer program code <NUM>) that controls the operation of the controller apparatus <NUM> when loaded into the processor <NUM>. The computer program instructions, of the computer program <NUM>, provide the logic and routines that enables the controller apparatus <NUM> to perform the methods illustrated in <FIG> The processor <NUM> by reading the memory <NUM> is able to load and execute the computer program <NUM>.

The controller apparatus <NUM> therefore comprises: at least one processor <NUM>; and at least one memory <NUM> including computer program code <NUM>, the at least one memory <NUM> and the computer program code <NUM> configured to, with the at least one processor <NUM>, cause the controller apparatus <NUM> at least to perform:.

As illustrated in <FIG> the computer program <NUM> can arrive at the controller apparatus <NUM> via any suitable delivery mechanism <NUM>. The delivery mechanism <NUM> can be, for example, a machine readable medium, a computer-readable medium, a non-transitory computer-readable storage medium, a computer program product, a memory device, a record medium such as a Compact Disc Read-Only Memory (CD-ROM) or a Digital Versatile Disc (DVD) or a solid state memory, an article of manufacture that comprises or tangibly embodies the computer program <NUM>. The delivery mechanism can be a signal configured to reliably transfer the computer program <NUM>. The controller apparatus <NUM> can propagate or transmit the computer program <NUM> as a computer data signal. In some examples the computer program <NUM> can be transmitted to the controller apparatus <NUM> using a wireless protocol such as Bluetooth, Bluetooth Low Energy, Bluetooth Smart, 6LoWPan (IPv<NUM> over low power personal area networks) ZigBee, ANT+, near field communication (NFC), Radio frequency identification, wireless local area network (wireless LAN) or any other suitable protocol.

The computer program <NUM> comprises computer program instructions for causing a controller apparatus <NUM> to perform at least the following:.

The computer program instructions can be comprised in a computer program <NUM>, a non-transitory computer readable medium, a computer program product, a machine readable medium. In some but not necessarily all examples, the computer program instructions can be distributed over more than one computer program <NUM>.

Although the memory <NUM> is illustrated as a single component/circuitry it can be implemented as one or more separate components/circuitry some or all of which can be integrated/removable and/or can provide permanent/semi-permanent/ dynamic/cached storage.

Although the processor <NUM> is illustrated as a single component/circuitry it can be implemented as one or more separate components/circuitry some or all of which can be integrated/removable. The processor <NUM> can be a single core or multi-core processor.

References to "computer-readable storage medium", "computer program product", "tangibly embodied computer program" etc. or a "controller", "computer", "processor" etc. should be understood to encompass not only computers having different architectures such as single /multi- processor architectures and sequential (Von Neumann)/parallel architectures but also specialized circuits such as field-programmable gate arrays (FPGA), application specific circuits (ASIC), signal processing devices and other processing circuitry.

As used in this application, the term "circuitry" can refer to one or more or all of the following:.

The blocks illustrated in <FIG> can represent steps in a method and/or sections of code in the computer program <NUM>. The illustration of a particular order to the blocks does not necessarily imply that there is a required or preferred order for the blocks and the order and arrangement of the blocks can be varied. Furthermore, it can be possible for some blocks to be omitted.

The systems, apparatus <NUM>, methods and computer programs <NUM> can use machine learning which can include statistical learning. Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. The computer learns from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E. The computer can often learn from prior training data to make predictions on future data. Machine learning includes wholly or partially supervised learning and wholly or partially unsupervised learning. It may enable discrete outputs (for example classification, clustering) and continuous outputs (for example regression). Machine learning may for example be implemented using different approaches such as cost function minimization, artificial neural networks, support vector machines and Bayesian networks for example. Cost function minimization may, for example, be used in linear and polynomial regression and K-means clustering. Artificial neural networks, for example with one or more hidden layers, model complex relationship between input vectors and output vectors. Support vector machines can be used for supervised learning. A Bayesian network is a directed acyclic graph that represents the conditional independence of a number of random variables.

The term 'a' or 'the' is used in this document with an inclusive not an exclusive meaning. That is any reference to X comprising a/the Y indicates that X may comprise only one Y or may comprise more than one Y unless the context clearly indicates the contrary. If it is intended to use 'a' or 'the' with an exclusive meaning then it will be made clear in the context. In some circumstances the use of 'at least one' or 'one or more' may be used to emphasis an inclusive meaning but the absence of these terms should not be taken to infer any exclusive meaning.

The presence of a feature (or combination of features) in a claim is a reference to that feature or (combination of features) itself and also to features that achieve substantially the same technical effect (equivalent features). The equivalent features include, for example, features that are variants and achieve substantially the same result in substantially the same way. The equivalent features include, for example, features that perform substantially the same function, in substantially the same way to achieve substantially the same result.

Claim 1:
An apparatus (<NUM>) comprising means for:
providing (<NUM>) a plurality of electrical input signals (<NUM>) to a biological sample (<NUM>);
receiving (<NUM>) a plurality of electrical output signals (<NUM>) from the biological sample (<NUM>) where the electrical output signals (<NUM>) correspond to the electrical input signals (<NUM>) and the values of the electrical output signals (<NUM>) are based on one or more electrical properties of the biological sample (<NUM>);
controlling (<NUM>) the electrical input signals (<NUM>) so that the plurality of electrical output signals (<NUM>) from the biological sample (<NUM>) comprise one or more general features and one or more sub-features where the one or more general features and the one or more sub-features enable one or more characteristics of the biological sample (<NUM>) to be identified;
wherein the one or more general features and the one or more sub-features comprise measurement points within the plurality of electrical output signals (<NUM>); and
wherein the one or more general features comprise one or more global minima or maxima within one or more of the electrical output signals (<NUM>) and the one or more sub-features comprise local minima or maxima within the one or more electrical output signals (<NUM>).