Patent Description:
Artificial somatosensory perception typically requires sensor arrays that can capture and process rapidly varying contact stimuli over non-uniform surfaces. Electronic skins (e-skins) are electronic devices that are arrayed to facilitate the sensing of human-machine-environment interactions with applications in advanced collaborative anthropomorphic robots and neuro-prosthetics. Although much progress has been made in developing compliant e-skin sensors with high sensitivity, known signal communication arrangements of such e-skin sensors have numerous disadvantages.

One known arrangement of the sensors relies on conventional Time Division Multiple Access (TDMA) architectures for signal communications, in which the sensors are sampled at a predetermined frequency or predetermined time slots. TDMA based sensor systems are known to have poor scalability because sequential data acquisition leads to a greater transmission latency in larger arrays. Further, the conventional row-column wiring for addressing individual sensors is prone to damage. In addition, highly localized and transient contact stimuli, such as a needle prick or an object slip, may be missed if the sensor sampling frequency is too low.

Another arrangement relies on Code Divisional Multiple Access (CDMA) techniques for wireless signal communications. CDMA is more complex due to the need for signal modulation from an intermediate frequency to a carrier frequency. Additional modules for power regulation are also required. Moreover, CDMA uses level shifted codes, which are relatively susceptible to low frequency interferences (e.g., AC power noises). Further, CDMA typically requires expensive high resolution ADCs. CDMA is also known to have a low capacity.

Another known arrangement involves Address Event Representations (AER). AER relies on asynchronous hand-shakes to time-multiplex data packets on a first-come-first-served basis. AER requires an implementation of arbitration logic in order to determine which packet to transmit first in the event of a packet collision, which results in a more complex network.

Optical CDMA is another known signal communication arrangement, known to use unipolar pulses and hence requiring additional synchronization signals and protocols. Dedicated electro-optical components are also required.

Yet another arrangement uses Ethernet. It does not support simultaneous packet transmission from a plurality of nodes. Further, transmission overheads (such as Carrier Sense Multiple Access) are needed to prevent packet collision, and multiple, separate conductors are needed to implement the protocols.

It is desirable to provide a sensor-based communication apparatus, a sensor-based communication method, and a communication medium, which address at least one of the drawbacks of the prior art and/or to provide the public with a useful choice.

<CIT> discloses a method including representing data using at least one pulse based on a Gaussian wave form, sending the at least one pulse over an electrically conductive guided media, and recovering the data from the at least one pulse.

<CIT> discloses a system which allows multiple senders to asynchronously transmit identification codes via a common communication channel (e.g., RF) to enable a central monitor to identify the presence (or absence) of each sender within the monitor's detection zone.

<NPL> discloses the use of a transmit-only mechanism for data transfer in wireless body area network (WBAN) applications.

<CIT> discloses apparatus and methods for encoding sensory input information into patterns of pulses and message multiplexing.

According to a first aspect, there is provided a sensor-based communication apparatus according to claim <NUM>.

The described embodiment is particularly advantageous. For example, since the sensor nodes are configured to transmit the respective pulse signatures independently with each trigger, i.e. on receipt of the stimulus, a highly efficient signalling scheme may be achieved. Since the described embodiment includes using event-based sensing elements responding to a single stimulus event, a resultant pattern in space and time may be used to represent the stimulus event.

Each inter-pulse interval of the unique pulse signature of each of the sensor nodes has a unique duration. Such an arrangement is useful in reducing the probability of collision of pulses transmitted by the sensor nodes.

The unique pulse signature may have between eight and fourteen pulses. An optimal performance of Signal to Interference and Noise Ratio (SINR) can be achieved when the number of pulses fall within or is close to this range.

Alternatively, the unique pulse signature of one of the sensor nodes may have a first number of pulses and the unique pulse signature of another of the sensor nodes may have a second number of pulses different from the first number. This arrangement allows the numbers of pulses to be flexibly determined, for example, based on the types and numbers of associated sensors.

Preferably, the unique pulse signature has a signature duration of <NUM> (millisecond). This allows the sensor nodes to mimic the transmission performance of the biological counterparts. The signature duration may also be adjusted to meet various capacity needs.

Alternatively, the unique pulse signature of one of the sensor nodes may have a first signature duration and the unique pulse signature of another of the sensor nodes may have a second signature duration different from the first signature duration. This arrangement allows the signature durations to be flexibly determined, for example, based on the types and numbers of associated sensors.

Preferably, the unique pulse signature may have a pulse duration of <NUM> ns (nanoseconds). This allows the sensor nodes to mimic the transmission performance of the biological counterparts. More preferably, the unique pulse signature may have a pulse duration shorter than <NUM> ns (nanoseconds) which may maximise capacity and minimise error rates.

Alternatively, the unique pulse signature of one of the sensor nodes may have a first pulse duration and the unique pulse signature of another of the sensor nodes may have a second pulse duration different from the first pulse duration. This arrangement allows the pulse durations to be flexibly determined, for example, based on the types and numbers of associated sensors.

Preferably, the apparatus further comprises the sensors. The apparatus may be manufactured so that each sensor node is integrated with or otherwise associated with a corresponding sensor. Where the apparatus does not comprise the sensors, the sensor nodes of the apparatus may be adapted to be associated with external sensors. The sensors may include tactile sensors of different sensitivities. By mixing sensors of different sensitivities, a more accurate, comprehensive representation of the stimulus event can be obtained. Further, the sensors may include temperature sensors. Other types of sensors may also be included such as electro-magnetic, humidity, surface texture, vibration, acceleration and/or optical sensors etc..

Preferably, each sensor node may be triggered, upon receiving a current value in the corresponding sensory signal, to transmit a current one of the associated unique pulse signature to indicate the current value by an interval between the current one of the associated unique pulse signature and a previous one of the associated unique pulse signature. This arrangement is useful when the sensor node is associated with a sensor which generates a sensory signal representing a current value of detection by the sensor. For example, the sensory signal may have a state representing the current value. A slow adapting (SA) sensor (or a piezoresistive resistive element configured to be a slow adapting sensor) is one such sensor.

The sensor nodes may be adapted to be associated with one of a robot, a human and a vehicle, or a robot may comprise such a sensor-based communication apparatus.

Preferably, the sensor nodes may harvest power from an external energy source. Such a source may be a source of electromagnetic waves, mechanical motions, solar energy, chemical substances, or the likes.

The apparatus may further comprise: a receiver configured to receive through the transmission medium an incoming signal relating to the transmitted unique pulse signatures, to correlate the associated unique pulse signature of each sensor node with an intermediate signal relating to the incoming signal, and to provide indication signals indicating respective times of triggering of the sensor nodes based on a result of correlation for representation of the stimulus event. The receiver may be locally or remotely located with respect to the sensor nodes.

Preferably, the receiver includes a plurality of filters each activated, upon detection of an edge in the incoming signal by the receiver, to correlate the intermediate signal with a corresponding one of the unique pulse signatures. This arrangement allows the filters to be activated to correlate the intermediate signal with the signatures in parallel when the edge is detected in the incoming signal. That is, the filters may remain deactivated to save power when no signature is transmitted (thus no edge). Other components (e.g., correlation threshold circuits) associated with the filters may be activated and deactivated correspondingly.

The transmission medium may include a conductive medium, and the sensor nodes may be distributed along the conductive medium and electrically coupled to one another through the conductive medium. Preferably, the sensor nodes are arranged on a surface of the conductive medium. Preferably, the sensor nodes are embedded in the conductive medium. Preferably, the conductive medium is made of polymer. Preferably, the conductive medium is elastic and flexible. Preferably, the conductive medium is mesh or planar in form. With one or more of such arrangements, signal communication via the conductive medium is resistant to damages such as tears. Communication between two portions of the conductive medium remains unaffected unless one portion is completely torn or otherwise removed from the other portion.

The conductive medium may include at least one of a conductive fabric, a conductive bulk conductor, a conductive substrate, a conductive solid, a conductive gel, and a conductive fluid. For example, when the conductive medium is implemented in the form of a fabric or substrate may be suitable for electronic skin applications. For the avoidance of doubt, "fluid" can include, but is not limited to, "liquid".

It is envisaged that each sensor node is associated with one or more unique pulse signatures. Preferably, each sensor node may be further associated with a further (or another) unique pulse signature. This arrangement is useful when the sensory signal of each sensor has two states. Each sensor node may be triggered, upon receipt of the corresponding sensory signal in a first state, to transmit the associated unique pulse signature, and upon receipt of the corresponding sensory signal in a second state, to transmit the associated further unique pulse signature independently through the transmission medium. The unique pulse signatures associated to each sensor node may correspond to or exceed the number of states in the corresponding sensory signal.

Each sensor node may be configured to transmit the associated further unique pulse signature independently through the transmission medium to indicate an internal state of the respective sensor node. This arrangement reduces the need for another communication path or channel for indicating the internal state.

Further, the unique pulse signatures of each sensor node may have different pulse polarities. For example, two signatures assigned to a sensor node may have the same pulse positions and opposite pulse polarities, where a pulse polarity is a positive or negative voltage potential. Further, two signatures of a sensor node may be otherwise different, either partially or wholly.

Advantageous, the representation of the stimulus event may be a spatiotemporal representation.

In a second aspect, there is provided a sensor-based communication method in accordance with claim <NUM>.

It is envisaged that features relating to one aspect may be applicable to the other aspects.

Example embodiments will now be described hereinafter with reference to the accompanying drawings, wherein like parts are denoted by like reference numerals. Among the drawings:.

<FIG> shows a schematic diagram of a sensor-based communication apparatus <NUM> according to an embodiment of the present disclosure. The apparatus <NUM> includes a communication medium <NUM> and a receiver <NUM>. In this embodiment, the communication medium <NUM> includes a layer of electronic skin shown in <FIG> covering or worn by a robotic hand.

<FIG> shows an enlarged partial isometric view of the communication medium <NUM>. The communication medium <NUM> includes a conductive fabric <NUM> (e.g., a conductive substrate or medium) and a plurality of sensor nodes <NUM> electrically attached to and embedded in the conductive fabric <NUM>. The sensor nodes <NUM> are associated with respective unique pulse signatures <NUM> and are adapted to communicate with respective sensors <NUM>. In this embodiment, each sensor node <NUM> is integrally formed with the corresponding sensor <NUM>, although this may not be the case in other embodiments. Each sensor <NUM> generates a sensory signal 113a (see <FIG>) upon detecting a respective stimulus 113b. In the present embodiment, each sensor <NUM> is a tactile sensor responsive to a touch or pressure to generate the sensory signal 113a. Each sensor node <NUM> is triggered, upon receipt of the corresponding sensory signal 113a from the respective sensor <NUM>, to transmit the associated unique pulse signature <NUM> independently through a transmission medium shared by the sensor nodes <NUM>. The transmission medium in this embodiment is the conductive fabric <NUM> of the communication medium <NUM>. In other embodiments, the transmission medium can be any medium shared by the sensor nodes <NUM>. For example, the transmission medium may be one capable of transmitting vibration/sound, optical, and/or magnetic field signals.

In particular, referring to <FIG>, each sensor node <NUM> further includes a digital pulse generator <NUM> associated with the respective sensor <NUM> (not shown in <FIG>). The digital pulse generator <NUM> includes a microcontroller <NUM> operatively associated with the corresponding sensor <NUM>, and a high-pass filter <NUM> arranged to filter an output of the microcontroller <NUM>. For each sensor node <NUM>, the microcontroller <NUM> includes a digital I/O pin moveable between three positions ("Vdd", "High Z" and "Vss") corresponding to positive, resting and negative potentials of the associated unique pulse signature <NUM>, respectively (see <FIG>). Instructions for generating pulses of the associated unique pulse signature <NUM> is pre-programmed into the microcontroller <NUM>. The instructions specify a sequence of pulses and a time interval between each adjacent pulse pair. The microcontroller <NUM> is triggered, upon receipt of the corresponding sensory signal 113a from the respective sensor <NUM>, to generate the pulses of the associated unique pulse signature <NUM> in real time by moveably switching the digital I/O pin in accordance with the pre-programmed instructions. This operation of the microcontroller <NUM> for signature generation based on the sensory signal 113a is indicated by the circle marked as "OP1" in <FIG>. In one arrangement, the microcontroller <NUM> (Attiny20™ by Microchip Technology™) includes a potential divider circuit for converting a sensor resistance indicated by the respective sensory signal 113a into a voltage. The voltage is then sampled at <NUM> with a <NUM>-bit resolution by an onboard Analog-to-Digital Converter (ADC) of the microcontroller <NUM>. The sampled values are sent to firmware models to mimic the fast-adapting (FA) or slow adapting (SA) behaviour of receptors found in the human skin, which is explained below. In other embodiments, instead of using a microcontroller to generate the respective pulse signature <NUM>, each sensor node <NUM> may use, for example, a mechanical (MEMS) switch or a custom electrical circuit to generate the respective pulse signature <NUM>.

The high-pass filter <NUM> is arranged to filter or condition the pulses generated by the microcontroller <NUM> to provide the corresponding unique pulse signature <NUM> for transmission through a gain adjustment resistor <NUM> associated with the respective sensor node <NUM> via the conductive fabric <NUM>. The high-pass filter <NUM> includes two resistors and a capacitor. The resistors are electrically connected in series between a positive supply voltage source used for the positive potential (marked as "Vdd") and a negative supply voltage source used for the negative potential (marked as "Vss"). The capacitor has a first end electrically connected to the digital I/O pin through a node between the resistors, and a second end connected to the conductive fabric <NUM> through the corresponding gain adjustment resistor <NUM>. The high-pass filter <NUM> is thus used to filter any direct current (DC) and low frequency components in the respective unique pulse signature <NUM>. The sensor nodes <NUM> may adopt any other suitable circuitry for pulse generation and filtering. The circuitry illustrated in <FIG> is advantageous due to its lower cost and power consumption.

The unique pulse signatures <NUM> thus transmitted by the sensor nodes <NUM> through the conductive fabric <NUM> are (or provide) a representation (e.g., a spatiotemporal representation) of a stimulus event associated with the stimuli 113b detected by the corresponding sensors <NUM>. In this embodiment, as illustrated in <FIG>, the stimulus event is the robotic hand holding a ball. More particularly, the unique pulse signatures <NUM> generated and transmitted by the respective sensor nodes <NUM> collectively serve as a basis for acquisition of a spatiotemporal representation of the stimulus event associated with the stimuli 113b detected by the corresponding sensors <NUM>. With knowledge of locations of the sensor nodes <NUM> (or the sensors <NUM>) and the respective times of triggering of the sensor nodes <NUM> (or of pressure detection by the sensors <NUM>), a spatiotemporal representation of the stimulus event can be accurately rendered. That is, the unique pulse signatures <NUM> transmitted in association with a stimulus event carry or preserve information temporally descriptive of detection of the respective stimuli by the respective sensors <NUM>. Combined with knowledge of locations (or relative locations) of the sensors <NUM> collocated with the respective sensor nodes <NUM>, a spatiotemporal representation of sensor stimulation can be rendered.

<FIG> shows the unique pulse signature <NUM> transmitted by one of the sensor nodes <NUM> through the conductive fabric <NUM>. In this embodiment, the unique pulse signature <NUM> is bipolar and transmitted independently and asynchronously by the respective sensor node <NUM>. Each inter-pulse interval of each unique pulse signature <NUM> has a unique duration (see <FIG>), and the unique pulse signature <NUM> has eight pulses, and a signature duration of <NUM> (millisecond), and the unique pulse signature <NUM> has a pulse duration of <NUM> ns (nanoseconds). Each neighbouring pair of pulses of each unique pulse signature <NUM> has a unique duration in the apparatus <NUM>. The total number of voltage pulses in a pulse signature <NUM> denotes a 'weight' of the pulse signature <NUM>. The signature duration of <NUM> specifies a maximum allowed time difference from the first voltage pulse to the last voltage pulse of a pulse signature <NUM>.

Referring again to <FIG>, the apparatus <NUM> further includes a summing circuit <NUM> electrically associated with the sensor nodes <NUM> and the receiver <NUM>. The summing circuit <NUM> includes an operational amplifier <NUM> with a noninverting input terminal that is grounded and an inverting input terminal that is electrically connected to the conductive fabric <NUM>. The summing circuit <NUM> further includes a parallel connection of a resistor <NUM> and a capacitor <NUM> electrically connected across the inverting terminal and an output terminal of the operational amplifier <NUM>, with the output terminal being connected to the receiver <NUM>. With such a configuration, the summing circuit <NUM> serves to filter or suppress any DC components in the unique pulse signatures <NUM> transmitted by the sensor nodes <NUM> and also to 'sum' or combine the unique pulse signatures <NUM> in time domain for transmission through the conductive fabric <NUM> for receipt by the receiver <NUM>. The summing circuit <NUM> may form part of the receiver <NUM> in other embodiments. In such a configuration, the summing circuit <NUM> may clip any portions of the summed or combined signatures <NUM> exceeding supply rails of the operational amplifier <NUM>, provided that the time position of each pulse in the summed or combined signatures <NUM> remains unaffected by the clipping operation. Depending on implementation, the summing circuit <NUM> may further include the resistors <NUM> and the conductive fabric <NUM>, such that the summing circuit <NUM> may be considered to be distributed across the transmission medium. As shown in <FIG> with respect to one of the sensor nodes <NUM>, in the distributed arrangement, the resistors <NUM> of the summing circuit <NUM> are arranged proximate to the respective sensor nodes <NUM> and distal from the other components <NUM>-<NUM> of the summing circuit <NUM>. In the current embodiment of <FIG>, the operational amplifier <NUM>, the resistor <NUM> and the capacitor <NUM> are disposed proximate or at the receiver <NUM> for consideration of convenience, size and power constraints.

<FIG> and <FIG> also show a representation of the unique pulse signatures <NUM> independently transmitted by the sensor nodes <NUM> to collectively form an incoming signal <NUM> to be received by the receiver <NUM> via the conductive fabric <NUM> through the summing circuit <NUM>. In the form of the incoming signal <NUM>, the signatures <NUM> may be considered to be combined or superposed since they are independently and asynchronously transmitted when the corresponding sensor nodes <NUM> are triggered. It can be seen that the pulses in the incoming signal <NUM> are mostly staggered. With reference to <FIG>, the receiver <NUM> includes a detection and digitisation circuit <NUM> and a plurality of filters <NUM>, which are digital filters in this embodiment. The detection and digitisation circuit <NUM> is arranged to detect an edge in the incoming signal <NUM>, to activate the filters <NUM> upon edge detection, and to perform analog-to-digital conversion on the incoming signal <NUM> to provide an intermediate signal <NUM>'. With this configuration, the filters <NUM> are activated only when an edge is detected in the incoming signal <NUM> by the detection and digitisation circuit <NUM>. Power consumption of the receiver <NUM> may thus be reduced. The receiver <NUM> may thus be particularly suitable for use in scenarios of sparse or infrequent stimulation events. As the transmitted signatures <NUM>, as discussed above, are a representation of the stimulus event, the incoming signal <NUM> resulting from the transmitted signature <NUM> may be considered to be a representation of the stimulus event.

Each of the filters <NUM> is configured to detect the unique pulse signature <NUM> of a respective one of the sensor nodes <NUM> in the intermediate signal <NUM>' to indicate a time of triggering of the respective sensor node <NUM> in association with the stimulus event. Specifically, each filter <NUM> is configured to perform a correlation operation (e.g., convolution or multiplication in time domain) on the intermediate signal <NUM>' with the corresponding unique pulse signature <NUM> to provide an indication signal <NUM> to indicate the corresponding time of triggering of the corresponding sensor node <NUM> in the form of a pulse ("indication pulse", <FIG>). This correlation operation is indicated by a circle marked as "OP2" in <FIG>. The indication signal <NUM> may be a continuous signal with the indication pulse at the time of high correlation to indicate the generation of the sensory signal 113a by the corresponding sensor <NUM>. The indication pulse may be a positive pulse representing a binary '<NUM>' or a negative pulse representing a binary '<NUM>'. In <FIG>, two positive indication pulses and one negative indication pulse are shown. In this example, irrespective of the polarity, a pulse in the indication signal <NUM> indicates a detection of tactile pressure by the corresponding sensor <NUM>. The unique pulse signatures <NUM> may be pre-programmed into the receiver <NUM> for use by the respective filters <NUM>.

As illustrated in <FIG>, the receiver <NUM> further includes a plurality of threshold circuit <NUM> associated with the filters <NUM>, respectively. Each threshold circuit <NUM> is configured to suppress an indication pulse in the corresponding indication signal <NUM> if the corresponding result of correlation operation is below a correlation threshold value. For example, with an example correlation threshold value of <NUM> (e.g., if the intermediate signal <NUM>' correlates concurrently with at least seven pulses of the respective signature <NUM> at a given time point), if the result of a correlation operation for a signature is <NUM> (i.e., below the correlation threshold value), the indication pulse generated by the corresponding filter is suppressed by the corresponding threshold circuit <NUM> due to the likelihood of error (i.e., low correlation). The correlation threshold value may be adjusted based on statistic values of, for example, the filters <NUM>. The indication signals <NUM> are then received by a computing device <NUM> for storage, presentation or any other use. Activation and deactivation of the threshold circuits <NUM> may depend on those of the respective filters <NUM>.

<FIG> shows three timing diagrams (i), (ii) and (iii) obtained using the apparatus <NUM> in another configuration involving six sensor nodes <NUM> associated with respective unique pulse signatures <NUM> of <NUM> pulses. The top pulse diagram (i) shows the incoming signal <NUM> received by the receiver <NUM> with the incoming signal <NUM> formed from pulse signatures <NUM> transmitted by the six sensor nodes <NUM> illustrated in pulse diagram (ii). The bottom diagram (iii) shows the indication signals <NUM> of the filters <NUM>, with the correlation threshold values of the threshold circuits <NUM> marked by the dash horizontal line. In the bottom diagram, each small circle marks a respective time point of high correlation where a result of correlation of the intermediate signal <NUM>' with the corresponding unique pulse signature <NUM>' exceeds the correlation threshold value of the respective threshold circuit <NUM>. It can be appreciated that the relative times of stimulus detection by the respective sensors <NUM> can be accurately determined or resolved based on the respective time points (i.e., the respective indication pulses) of high correlation. For instance, referring to <FIG>, signature transmission by Node <NUM> occurs <NUM> earlier than that by Node <NUM>. A conventional time multiplexed system cannot achieve such a level of temporal resolution without adopting a frame rate in the megahertz range, which is not possible in most practical situations involving large arrays of sensors. For instance, a conventional <NUM> element slip detection array with a <NUM> sampling rate is considered a very high speed sensor array by the current standard, and can only achieve a temporal resolution of approximately <NUM>, which is at least <NUM> times slower than the sampling rate achievable with the apparatus <NUM>.

<FIG> is a diagram showing transmission of unique pulse signatures <NUM> by five sensor nodes <NUM> in association with a stimulus event to illustrate the spatiotemporal nature of the stimulation event. By way of illustration, the first pulse of each signature <NUM> is marked by a hollow circle AA, and each hollow circle AA is linked by a respective dashed line BB to another hollow circle AA. This is an example spatiotemporal representation of stimulation of respective sensors <NUM> in association with the stimulus event (e.g., a touch). In this particular example, the unique pulse signature <NUM> of each sensor node <NUM> begins with a positive pulse. The first pulse of each signature <NUM> transmitted in association with the stimulus event can thus indicate a relative time point of triggering of the respective sensor node <NUM> by the sensory signal 130a of the respective sensor <NUM>.

<FIG> shows the signatures <NUM> of <FIG> combined to form an incoming signal <NUM> for receipt by the receiver <NUM>. <FIG> shows indication signals <NUM> corresponding to the sensor nodes <NUM> of <FIG>, provided by the receiver <NUM> based on the incoming signal <NUM> of <FIG>. For each sensor node <NUM>, each hollow circle AA marks a time point where a result of correlation between the corresponding unique pulse signature <NUM> and the intermediate signal <NUM>' exceeds the correlation threshold value marked by the corresponding shaded area. Each hollow circle AA is shown to be connected by a respective dashed line BB to another hollow circle AA to illustrate the spatiotemporal nature of the signal. It can be appreciated that the relative time points of the hollow circles AA in <FIG> are similar or identical to those shown in <FIG>. This means that a spatiotemporal pattern of sensor stimulation can be represented with reference to the time points of high signature correlation. Thus, with knowledge of physical locations of the sensors <NUM> (or of the sensor nodes <NUM>), a spatiotemporal representation of the stimulus event can be rendered based on the relative time points of high correlation.

<FIG> illustrates an example spatiotemporal representation <NUM> of a stimulus event associated with stimuli detected by the sensors <NUM> based on the indication signals <NUM> in another scenario. In this example, the communication medium <NUM> is implemented in the form of electronic skin (or a thin glove) and is worn on the right hand of a human user pinching a solid round object <NUM>. Based on the indication signals <NUM> and knowledge of locations (either relative or absolute) of the sensor <NUM>, times (or time points) of tactile pressure detection by the respective sensors <NUM> can be spatiotemporally represented.

At time point t-<NUM>, the communication medium <NUM> is not yet in contact with the object <NUM>. A non-detection status of each sensor <NUM> is marked by a small hollow circle <NUM>.

At time point t<NUM>, the communication medium <NUM> comes into contact with the object <NUM>, and a small portion of the sensors <NUM> detect tactile pressure as a form of stimulus 113b, where a detection status of each sensor <NUM> is marked by a small solid circle <NUM>. For each sensor <NUM> of the detection status, the resultant indication pulse <NUM> in the corresponding indication signal <NUM> is shown on a corresponding horizontal line. A distance between the indication pulse <NUM> and the corresponding solid small circle <NUM> along the corresponding horizontal line is proportional to an amount of elapsed time since pressure detection by the corresponding sensor <NUM>. That is, the indication pulse <NUM> moves towards the right along the corresponding horizontal line as time passes.

At time point t<NUM>, the communication medium <NUM> deforms and a larger portion of the sensor nodes <NUM> come into contact with the round object <NUM>, indicated by more indication pulses <NUM>, <NUM>. It can be seen that the indication pulses <NUM> generated by the small portion of the sensor nodes <NUM> at time t<NUM> have moved further to the right, indicating that more time has elapsed since the pressure detection by the sensors <NUM> of those indication pulses <NUM>.

At time point t<NUM>, the communication medium <NUM> deforms more as the grip force on the round object <NUM> increases and an even larger portion of the sensor nodes <NUM> come into contact with the object <NUM>, indicated by even more indication pulses <NUM>-<NUM>. A clear spatiotemporal pattern formed by the generated indication pulses <NUM>-<NUM> and representing the stimulus event of pinching the round object <NUM> can be clearly observed.

<FIG> shows another pulse signature with <NUM> pulses (weight, W, of <NUM>) after quantisation, with the first pulse marked by a rectangular box. 'V+' and 'V-' mark the quantization thresholds for pulse detection, respectively.

<FIG> shows a diagram of temporal precisions of the indication signals <NUM> versus numbers of overlapping pulse signatures <NUM>, for different numbers of pulses (or weights, W) in each signature <NUM>, obtained with <NUM> sensors in an actual experiment. The shaded regions indicate respective standard deviations. The output of the receiver <NUM> maintains the relative time differences of the transmitted unique pulse signatures <NUM> with a temporal precision of <NUM> ns or less. The transmission latency is also constant, dependent only on the duration of the pulse signature <NUM> and not the number of sensor nodes <NUM>.

<FIG> shows relationships between correlation threshold values and detection error probabilities (transmission error rate) with a weight, W, of <NUM>. With <NUM> simultaneously transmitting sensor nodes <NUM> (simultaneous transmission for ensuring the occurrence of collision) and a correlation threshold value of <NUM>, a false positive probability of <NUM> (<NUM>%) and a missed detection probability of <NUM> (<NUM>%) can be achieved. Using a Monte Carlo simulation , even with <NUM> overlapping signatures <NUM>, it is possible to achieve a probability of false positive detection of <NUM> (or <NUM>%) or a probability of missed detection of <NUM> (or <NUM>%). Given the typically sparse nature of tactile events, the probability of <NUM> overlapping signatures <NUM> is expected to be low. The dashed lines in <FIG> represent simulation results. The result of <FIG> is obtained, with a <NUM>% confidence bounds. In the simulation of <FIG>, each sensor node <NUM> transmits a single symbol (i.e., pulse). The extent of overlap between any two symbols takes a uniform random distribution from a minimum of <NUM> pulse width to a maximum of the entire signature duration. The polarity of the transmitted symbol is also randomly assigned. The codes (i.e., signatures <NUM>) used in this simulation have a maximum auto and cross-correlation value of <NUM>. Pulse widths are of <NUM> ns in duration and all pulse signatures <NUM> have a duration of <NUM>. <NUM>,<NUM> Monte-Carlo trials are conducted for each combination of signature weights (i.e., the number of pulses in each signature <NUM>) and number of sensor nodes.

<FIG> shows a diagram of Signal to Interference and Noise Ratio (SINR) of the output (i.e., the indication signals <NUM>) of the receiver <NUM> versus the number of overlapping signatures <NUM> with a weight, W, of <NUM> and a pulse width of <NUM> ns. In <FIG>, the dashed line indicates results by Monte-Carlo simulation and the line marked by squares indicates actual results and shows a trend similar to that of the dashed line.

<FIG> shows a diagram of SINR of the output of the receiver <NUM> versus the number of overlapping signatures <NUM>, obtained for different pulse widths using simulation. It can be appreciated that the SINR of the output of the receiver <NUM> can be improved by reducing the pulse width or duration.

<FIG> shows a diagram of SINR of the output of the receiver <NUM> versus the number of overlapping signatures <NUM>, obtained for different weights (i.e., numbers of pulses in each signature <NUM>) using simulation based on a pulse width of <NUM> ns. While larger signature weights (W) improves SINR substantially where the number of overlapping signatures is less than <NUM>, the opposite is true where the number of overlapping signatures is higher. Therefore, a weight of <NUM> may be optimal.

The SINR characterizes the separability of a stimulus detection from interference, based on the output of the receiver <NUM>. In an experiment, a physical hardware test setup with an array of two hundred and forty sensor nodes, each programmed with a unique pulse signature, is developed to determine the SINR. Each trial begins with an external digital edge signal that is broadcast to all sensor nodes to triggering the sensor nodes to transmit the respective pulse signatures after a random delay of less than <NUM>. This ensures that the two hundred and forty transmitted signatures will overlap at varying temporal offsets between trials. For trials involving less than two hundred and forty sensor nodes, the excluded sensor nodes may be programmed to ignore the trigger.

Sixteen of the two hundred and forty sensor nodes have probes attached to their transmission pins (digital pins), respectively. Signals from these probes serve as the ground truth on the actual time and polarity of the pulses transmitted. The digital signals from these sixteen probes, as well as the combined pulse signatures from the two hundred and forty sensor nodes are digitized at <NUM> simultaneously by a mixed signal oscilloscope (Picoscope 3406D), thus ensuring that all channels are synchronized in time.

The SINR is computed for the receiver <NUM> associated with the sixteen probed sensor nodes. An interference value is computed as the root-mean-squared (RMS) value of the receiver output as the corresponding sensor node transmits its pulse signature. The last <NUM> ns of the receiver output is excluded from the RMS computation, since it corresponds to the detection of the correct pulse signature and should not be considered as interference. SINR is then computed as the ratio between the signature weight W and the interference value. For each network size, <NUM> trials were conducted, and the reported SINR is averaged from the <NUM> receivers across all <NUM> trials.

Timing precision is obtained as the difference in time between the start of last pulse transmission, as obtained from the attached probe, and the transmission time as determined from the output of the receiver. The reported timing precision in <FIG> is obtained as an average across all the <NUM> trials for each network size.

<FIG> shows a flowchart of an example algorithm or method <NUM> which may be used for generating the pulse signatures <NUM> for the apparatus <NUM>. The method <NUM> includes steps <NUM> to <NUM>, where step <NUM> includes sub-steps <NUM> to <NUM>.

Step <NUM> includes creating a database to store the unique pulse signatures <NUM> to be associated with the sensor nodes <NUM>, and is followed by step <NUM>.

Step <NUM> includes generating a family or set of signatures <NUM> by performing sub-steps <NUM> to <NUM>.

Sub-step <NUM> includes determining whether enough pulses have been generated to form a unique signature <NUM> of a specified weight, ending step <NUM> and proceeding to step <NUM> if affirmative, and proceeding to sub-step <NUM> if otherwise. The effect of the determination of sub-steps <NUM> is to ensure that the pulse positions of the signature <NUM> being generated are iteratively searched to make sure that duplicate temporal features are not used within the family of signatures <NUM> and that the pulse sequence being generated meets the specified weight.

Sub-step <NUM> includes adding a new pulse at random time within the specified signature duration, and is followed by sub-step <NUM>.

Sub-step <NUM> includes checking the pulse sequence of the current signature <NUM> being generated against the created database for any duplicate sequence in the database, and is followed by sub-step <NUM>.

Sub-step <NUM> includes determining whether a duplicate sequence has been found in the database in sub-step <NUM>, proceeding to sub-step <NUM> if affirmative, and proceeding to sub-step <NUM> if otherwise.

Sub-step <NUM> includes removing the most recently added pulse in the signature <NUM> being generated, and is followed by sub-step <NUM>.

Sub-step <NUM> includes updating the created database with the current pulse sequence as a new signature <NUM> (i.e., adding the current pulse sequence as a new signature <NUM>), and is followed by sub-step <NUM>. The effect of sub-step <NUM> is to update the database with the current pulse sequence resulting from the addition of the current pulse, so that, if the next determination in sub-step <NUM> is negative, the search for the next pulse position in sub-step <NUM> uses the current pulse sequence in the updated database.

In such a manner, each signature <NUM> generated in step <NUM> is unique in the database.

Step <NUM> includes determining whether a new signature <NUM> has been found, proceeding to step <NUM> if affirmative, and proceeding back to step <NUM> if otherwise.

Step <NUM> includes determining whether enough signatures <NUM> have been found for the sensor nodes, ending the process if affirmative, and proceeding back to step <NUM> if otherwise.

Step <NUM> may be combined with step <NUM> if step <NUM> is modified to iterate an endless loop for signature generation, to be terminated after a certain period of time to start over. It is envisaged that some of the steps and sub-steps of the method <NUM> may be modified, combined, or omitted, provided that unique pulse signatures <NUM> can be generated.

With the use of this algorithm of <FIG>, autocorrelation and cross-correlation may be reduced whilst allowing enough unique pulse signatures <NUM> to be assigned to the sensor nodes <NUM>. With the number of signatures <NUM> being larger than or equal to the number of the sensor nodes <NUM>, a family of pulse signatures may be characterized by three parameters Φ(F, ω, λ), where:.

With F and ω determined, the temporal position of each individual pulse in each signature can then be determined to meet λ. For the computation of λ, consider two pulse signatures, s and s', both with ω = <NUM> and having pulses at times {τ<NUM>, τ<NUM>, τ<NUM>, τ<NUM>} and {τ'<NUM>, τ'<NUM>, τ'<NUM>, τ'<NUM>} respectively. Convolution of s with s' results in at least <NUM> overlapping pulse, giving λ ≥ <NUM>. However, the pulse signatures can be designed to have, at most, one overlapping pulse. This can be achieved by ensuring that each inter-pulse interval in each pulse signature is unique, as is the case with the embodiment of <FIG>. In the case of s and s', there are <NUM>C<NUM> (i.e., six) inter-pulse intervals per signature. To achieve λ = <NUM>, all <NUM> inter-pulse intervals (from s and s') must be unique.

Expanding to a case where λ > <NUM>, the concept of temporal pulse features Pλ is introduced. For example, if λ = <NUM>, the feature P<NUM> will have two elements {ρ<NUM>, ρ<NUM>}, where ρ<NUM> and ρ<NUM> are an ordered pair of inter-pulse intervals. In the case of s and s', there are <NUM>C<NUM> (i.e., four) P<NUM> features per signature. To ensure λ = <NUM>, all P<NUM> features in the family should be unique. The same approach can be applied to cases of λ > <NUM>. An example of pulse signatures at two different nodes is illustrated in <FIG>. An apparatus with a theoretical probability of error of zero can be achieved by ensuring that ω > nλ, where n is the number of signatures in the family. The design of the pulse signatures is discussed in further details below.

In the example of <FIG>, each sensor <NUM> only needs to indicate one state of detection in its sensory signal 113a upon pressure detection. Accordingly, each sensor node <NUM> is correspondingly associated with one unique pulse signature <NUM> to indicate the state of detection, and the respective filter <NUM> is also associated with the corresponding unique pulse signature <NUM> to perform the needed correlation operation. As a result, with each pressure detection by the sensor <NUM>, an indication pulse <NUM> of either polarity is generated to indicate the state of detection by the respective sensor <NUM>. For this particular example, polarity of the indication pulse may not represent useful information. However, in other embodiments, the polarity may be relevant. For example, two pulse signatures <NUM> of the same pulse positions and different (e.g., opposite) pulse polarities may be used by each sensor node <NUM> to indicate respective two states in the corresponding sensory signal 113a. The polarity of each pulse, or "pulse polarity", means the potential of the pulse, either the positive voltage potential ("Vdd") or the negative voltage potential ("Vss"). For parallel correlation operations, the number of filters <NUM> should match the total number of unique pulse signatures <NUM> assigned to the sensor nodes <NUM>.

It would be appreciated that the sensor nodes <NUM> may be associated with any other types of sensors <NUM>, such as temperature sensors, which may be integrated with the respective sensor nodes. Further, the sensor nodes <NUM> may be associated with more than one types of sensors (e.g., pressure and temperature sensors). For example, in an electronic skin application, the sensors <NUM> include an array of fast-adapting (FA) pressure sensors, slow-adapting (SA) pressure sensors and temperature sensors. Together, these sensors <NUM> may be configured to mimic the biological counterparts.

The FA sensors <NUM> are configured to respond only to dynamic deformation of the conductive fabric <NUM> and to be insensitive to static forces. Each FA sensor <NUM> is configured to indicate a first state of pressure increase and a second state of press decrease in its sensory signal 113a. That is to say, for each FA sensor <NUM>, the sensory signal 113a generated by the FA sensor <NUM> has the first and second states. The corresponding sensor node <NUM> of each FA sensor <NUM> is associated with first and second unique pulse signatures <NUM> to indicate the first and second states of the sensory signal 113a, respectively. Specifically, with the firmware of the sensor node <NUM> configured to recognise the corresponding FA sensor <NUM>, the firmware model in the sensor node <NUM> for the FA behaviour causes the microcontroller <NUM> to generate and transmit the first and second unique pulse signatures <NUM> according to the state of the corresponding sensory signal 113a. Each sensor node <NUM> is triggered, upon receipt of the corresponding sensory signal 113a in the first state, to transmit the associated first unique pulse signature <NUM>, and upon receipt of the corresponding sensory signal 113a in the second state, to transmit the associated second unique pulse signature <NUM> independently through the transmission medium. More specifically, in one particular example, the microcontroller <NUM> is caused by the firmware model to generate and transmit the first unique pulse signature <NUM> for each increment of more than <NUM> mV detected in the corresponding sensory signal 113a, and to generate and transmit the second unique pulse signature <NUM> for each decrement of more than <NUM> mV detected in the corresponding sensory signal 113a. With such a configuration, the sensor node <NUM> of each FA sensor <NUM> is able to indicate to the receiver <NUM> the state of the sensory signal 113a (increase and decrease of pressure). Moreover, as discussed above, the first and second unique pulse signatures <NUM> of each sensor node <NUM> may have different (e.g., opposite) pulse polarities. That is to say, the first and second pulse signatures <NUM> may have the same pulse positions but opposite pulse polarities (i.e., voltage potentials). In other embodiments, the first and second signatures <NUM> may be partially or completely different in terms of, for example, pulse position, pulse duration, inter-pulse duration, pulse polarity, the number of pulses, or a combination thereof. Contrary to the biological counterparts which do not distinguish between pressure increase and pressure decrease, the arrangement of the FA sensors <NUM> and the respective sensor nodes <NUM> can meet a wide range of temporal response requirements, from precise pressure or force measurements to transient tactile stimulus detection. Each sensor node <NUM> may, in other arrangements, be associated with a sensor <NUM> of any type, and be associated with unique pulse signatures corresponding in number to states of the sensory signal 113a generated by the sensor <NUM>.

The SA sensors <NUM> are further configured to respond to static pressure and to be insensitive to dynamic deformation of the conductive fabric <NUM>. Each SA sensor <NUM> is configured to indicate a current value of static pressure in its sensory signal 113a, and the corresponding sensor node <NUM> transmits the corresponding signature <NUM> at a frequency dependent on the current value. In this embodiment, the signature transmission frequency is in a positive relative to the current value of detected static pressure in the sensory signal 113a. That is, the higher the current value of detected pressure, the shorter the interval between two corresponding consecutive signature transmissions. In particular, the firmware model for SA behaviour causes the microcontroller <NUM> to generate and transmit multiple instances of the respective unique pulse signature <NUM> with an interval proportional to the <NUM> point averaged ADC digital value. For <FIG> and <FIG>, the interval is the sum of <NUM> and a product of <NUM> and the converted digital value in decimal. For example, to represent a value of <NUM>, two consecutive signatures are transmitted with an interval of <NUM> (<NUM> x <NUM> + <NUM>). Together with a <NUM> pulse signature duration, a maximum ADC value of <NUM> will correspond to a <NUM> interval between two consecutive signatures. The sensor node <NUM> of each SA sensor <NUM> needs to be associated with one unique pulse signature <NUM> to indicate a current value of detected pressure in its sensory signal. To indicate the current value, the associated sensor node <NUM> is configured to, having transmitted a previous one of an assigned unique pulse signature <NUM>, transmit a current one of the same unique pulse signature <NUM> to indicate the current value of detected static pressure by the interval between the transmitted current and previous ones of the assigned signature <NUM>. Upon initiation where the sensor node <NUM> has not transmitted the assigned signature <NUM> in association with a stimulus event, the sensor node <NUM> may indicate a first value of detected pressure by consecutively transmitting two instances of the corresponding signature <NUM> with an interval corresponding to the first value. Any subsequent values of detected static pressure may be indicated by the sensor node <NUM> in the manner described above. Each sensor node <NUM> may, in other arrangements, be associated with a sensor <NUM> of any type, and be configured to transmit consecutive instances of an associated unique pulse signature <NUM> to indicate, by a corresponding interval between current and previous ones of the associated unique pulse signature <NUM>, a current value of the sensory signal 113a generated by the sensor <NUM>.

It is worth noting that each sensor node <NUM> is, in the example of <FIG>, configured by way of firmware to recognise and be associated with the respective sensor <NUM>. That is, the sensor node <NUM> chooses a mode of operation based on the type or configuration of the associated sensor <NUM> (SA or FA). Whilst the FA and SA sensors <NUM> are described to be different types of sensors, they may be implemented using the same component (e.g., a piezoresistive element). In such a case, whether the sensor <NUM> is to function or be treated as an FA sensor or an SA sensor can be determined by the firmware of the respective sensor node <NUM>.

In another embodiment, each sensor node <NUM> is configured to transmit another associated unique pulse signature <NUM> independently through the transmission medium to indicate an internal state of the respective sensor node. For example, the sensor node <NUM> may be associated with one or more additional unique pulse signatures for each additional internal state to be reported.

<FIG> shows a plot of dynamic force increases and decreases sensed by one of the FA sensors <NUM> in relation to a load cell over time, and a plot of static forces detected by one of the SA sensors <NUM> against the load cell over time, obtained based on the corresponding indication signals <NUM> shown in <FIG>. For the FA sensor <NUM>, the detected states of force increase and force decrease are marked by opposite respective triangular symbols. For the SA sensor <NUM>, the values of detected static force are marked by respective square symbols. In the example of <FIG>, the SA sensors <NUM> can accurately detect static force and indicate the respective detected values in their respective sensory signals 113a. The FA sensors <NUM> can accurately detect dynamic force and indicate the detected states of force increase and force decrease in their sensory signals 113a. This is demonstrated in <FIG>, where the FA sensor <NUM> successfully detects force changes associated with a prick from a lancet lasting about <NUM>. The SA sensor <NUM> in this embodiment is not sensitive enough to detect the prick because the duration of the prick of <NUM> is well below the corresponding interval for indication of the force intensity. Both the SA and FA sensors <NUM> successfully detect a finger press taking place prior to the prick, as shown in <FIG>. The readings of the load cell are smoothed using a moving average filter of <NUM> points (OriginLab <NUM>). It should be noted that the term "force" as used in this context may be interpreted to include "pressure".

<FIG> show photographic representations of flexible pressure sensors implemented with heterogeneous transduction profiles developed by altering the Young's modulus of elastomers used to construct the micro-pyramidal piezo-resistive sensors. <FIG> shows a plot of resistance values versus pressures. This allows sensors of various tactile sensitivities to be distributed spatially on the same substrate (i.e., the conductive fabric <NUM>). With such a construction, the sensors can be made to be sensitive to both light touches and higher loads without saturation. The wide dynamic pressure range enables continued pressure detection under typical manipulation forces when gripping an object.

<FIG> shows a photographic representation of an array of pressure and temperature sensors on a robotic effector in the shape of a human hand in association with a cup of hot liquid. <FIG> shows a plot of resistivity versus temperature obtained using the temperature sensors of <FIG> shows an optical microscopic image of one of the temperature sensors of <FIG>. The temperature sensors are flexible resistive sensors implemented on a single substrate (i.e. conductive fabric). The temperature sensor is designed to have a main sensitivity range from <NUM> to <NUM>, which similar to the cold receptor afferents in human skin. The associated sensor node transmits the unique pulse signature at a reduced frequency (i.e., increased interval) as the detected temperature rises above <NUM> (see <FIG> shows an example arrangement of resistive pressure and temperature sensors on a single substrate (i.e., conductive fabric). <FIG> show diagrams in relation to the application of <FIG> (holding a cup containing hot liquid). <FIG> shows a diagram of indication signals versus time obtained from pulse signatures transmitted by the temperature and pressure (SA) sensors. <FIG> shows a diagram of stimulation detection based on the indications signals shown in <FIG>. It can be seen from these figures that simultaneous or near simultaneous detection of tactile and thermal stimuli by the SA and temperature sensors can be achieved.

In another application, the FA sensors <NUM> can be employed by, for example, a robotic effector to detect slippage of an object held by the effector. <FIG> (part i) shows a spatiotemporal representation or pattern of tactile stimuli detected by the FA sensors <NUM> over time, with the FA sensors <NUM> provided on the effector. A spiking convolutional network is implemented to compute the magnitude and direction of slippage in an event-driven manner. As slippage of the object starts to occur, stimulus detection by the FA sensors <NUM> triggers the computation of movement to estimate the onset of slippage.

Referring to <FIG>, movement estimates can be calculated immediately upon slippage onset, and the downward movement of the object can be accurately identified. <FIG> shows that the same implementation can be used to detect the slippage of a needle with <NUM> of latency. However, the directional estimates show higher deviations due to the smaller number of stimulated FA sensors <NUM> and the reduced contact area. Higher sensor densities are thus required for dextrous manipulation tasks of varying object form factor.

Specifically, in the experiments of <FIG> and <FIG>, an acrylic disk of <NUM> diameter and a needle of <NUM> diameter is held respectively and vertically between two flat opposing surfaces of a bench vice. An array of <NUM> pressure sensors (similar to the one in <FIG> but without the thermal sensors), are arranged to interface with a corresponding array of sensor nodes mimicking FA behaviour. The sensors are pasted on one of the surfaces of the vice. A thread connects the object to a load cell. A separate thread is connected to the opposite side of the load cell and adapted to be pulled to cause slippage of the object from the vice. Data generated by the <NUM> sensor nodes is sampled together with an analog output of the load cell at <NUM> using an oscilloscope (Picoscope 3406D). Computation of slip detection is processed offline in MATLAB.

The computation of local movement estimates (part ii, <FIG>) is generally as follows:.

The global movement estimate (part iii, <FIG>) is obtained as the moving average (exponential kernel of <NUM> time constant) for all the local movement estimates. For <FIG> and <FIG>, Δt = <NUM> and D = <NUM>.

<FIG> show another application where an array of <NUM> FA sensors mimic Meissner corpuscle responses. It can be appreciated that various local curvatures can be classified up to <NUM> times faster (within <NUM> with a <NUM>% accuracy) than possible with a <NUM> frame-per-second (fps) conventional sensor array.

Each of <FIG> shows a diagram of classification accuracy for two objects of identical geometrical features and different hardness, in another application of the FA sensors of <FIG>. <FIG> shows a diagram of classification accuracy for soft objects of different geometrical features of the same hardness. The results demonstrate the importance and effectiveness of temporal features in rapid tactile discrimination.

<FIG> show the conductive fabric (or conductive substrate) <NUM> of the communication medium <NUM> in intact and damaged states, respectively. It can be seen that signal communication of the sensor nodes <NUM> through the conductive fabric <NUM> remains unaffected despite two tears formed in the conductive fabric <NUM> (labelled as "Torn edges" in <FIG>). A signal conducting path between the receiver <NUM> and a most distal one of the sensor nodes <NUM> is shown (marked as "Signal path remains"). Also shown in <FIG> is a removed portion of the conductive fabric <NUM> (labelled as "Hole in substrate"). Two of the sensor nodes <NUM> (marked by respective dashed squares and labelled as "Nodes removed") corresponding to the removed portion are removed altogether. A skilled person would appreciate that the conductive fabric <NUM> thus provides multiple signal conducting paths between the receiver <NUM> and each of the sensor nodes <NUM>. Importantly, communication is adversely affected only if all signal conducting paths between the receiver <NUM> and the respective sensor node <NUM> are lost. That is to say, communication of a sensor node <NUM> in a portion of the conductive fabric <NUM> remains unaffected unless the portion of the conductive fabric <NUM> is completely torn apart or otherwise removed from the remaining portion of the conductive fabric <NUM>. In most cases, a partial tear in the conductive fabric <NUM> would not adversely affect communication of the sensor nodes <NUM> via the conductive fabric <NUM>. That is, signal communication between each of the sensor nodes <NUM> and the receiver <NUM> remains unaffected provided that the conductive fabric <NUM> can still provide at least one signal conducting path between the respective sensor node <NUM> and the receiver <NUM>. Communication of the sensor node <NUM> is thus robust to damage (e.g., physical damage) of the conductive fabric <NUM>.

In the example of <FIG>, the conductive fabric <NUM> is made of a conductive polymer (e.g., PEDOT:PSS). However, in other embodiments, any conductive medium (e.g., conductive knitted wires, carbon based nanomaterials, metal nanowires, metal films, and metal wires) may be used in place of or in conjunction with the conductive fabric <NUM>. The conductive fabric <NUM> of this example is electrically connected to the sensor nodes <NUM>. It is to be emphasized that the conductive fabric <NUM> is just one possible form of the conductive medium. Some other example forms are described below with reference to <FIG> and <FIG>. By virtue of the polymer configuration, the conductive fabric <NUM> provides (or can be considered to provide) multiple signal conducting paths for each of the sensor nodes <NUM> and, in this embodiment, also acts as a structural support to support the sensor nodes <NUM>. The conductive fabric <NUM> is elastic and flexible, thus suitable for electronic skin applications. The conductive fabric <NUM> thus allows for a flexible arrangement of the sensor nodes <NUM>, and signal communication is resistant to or unaffected by damage sustained by the conductive fabric <NUM>. The sensor nodes <NUM> can be flexibly configured in terms of placements, density and distribution to meet various design and application requirements. The conductive fabric <NUM> is thus suitable for covering or providing, for example, a curved surface of a humanoid robot for sensing non-uniform features.

<FIG> illustrates another communication medium <NUM>' which is a variant of the communication medium <NUM>. This communication medium <NUM>' includes a mesh/planar conductor portion <NUM>' associated with the sensor nodes <NUM>. In this example, each sensor node <NUM> is powered by a respective power source (e.g., a battery). Communication between each sensor node <NUM> and the receiver <NUM> remain unaffected so long as at least one signal path exists therebetween. In addition, the mesh/planar conductor portion <NUM>', if made to be elastic, are easier to realise in comparison with patterned wires (see <FIG>). Similar to the polymer configuration of <FIG>, the mesh/planar conductor portion <NUM>' provides substantial redundancy in signal conducting paths between each sensor node <NUM> and the receiver <NUM>.

The sensor nodes <NUM> in the example of <FIG> wirelessly harvest power from a source <NUM> of electromagnetic waves (e.g., power transmission coils), which may be incorporated in an underlying rigid structure of, for example, a robotic/prosthetic body portion, enabling flexible distribution of the sensor nodes <NUM> along the mesh/planar conductor portion <NUM>'. The sensor nodes <NUM> in other embodiments may also be configured to harvest power in a similar manner. In addition, other forms of power harvesting techniques (mechanical, solar, chemical, and thermal, etc) may also be employed to power the sensor nodes <NUM> wirelessly. The sensor nodes <NUM> may also be provided with respective power storage means (e.g., a rechargeable battery or a capacitive element) to store the harvested power.

<FIG> show two alternative embodiments of a basic setup of the communication medium <NUM>" where sensor nodes <NUM> are embedded in elastomeric material. In the embodiment of <FIG>, the sensor nodes <NUM> are powered by a common power supply. Each of the sensor nodes <NUM> and the receiver <NUM> is connected by a respective conductor <NUM>" (e.g., a wire) connecting to a common connection node. In such a configuration, each sensor node <NUM> requires only a single conductor <NUM>" for communication. The configuration of <FIG> differs from that of <FIG> only in that each sensor node <NUM> is associated with a respective power source (e.g., a battery). Although this configuration of the conductor <NUM>" reduces wiring complexity by virtue of the common connection node, it is not as robust as the configurations of <FIG> in terms robustness of signal communication to damage.

It should be appreciated that, in other embodiments, the conductive medium may include at least one of a conductive fabric, a conductive bulk conductor, a conductive substrate, a conductive solid, a conductive gel, and a conductive fluid. An example of conductive fluid is Galinstan, a liquid metal made from gallium, indium and tin. It is possible to construct a mesh of micro-fluidic channels in a stretchable polymer and fill it with Galinstan to achieve a highly flexible/stretchable substrate.

Wiring simplicity in certain applications (e.g., e-skin) is critical, especially when wires are to be routed along non-uniform surfaces or curvatures. <FIG> shows nine sensor nodes with respective integrated FA sensors in three different spatial formations, placed on a conductive fabric (knit jersey conductive fabric, Adafruit) and powered by respective internal batteries. In each of the irregular formations, the FA sensors can accurately detect respective stimuli, allowing a spatiotemporal representation to be obtained and demonstrating the ability of the sensor nodes to be used in environments of non-uniform or uneven geometries. In particular, to apply pressure, a conductive rod <NUM> is pressed against some of the sensors in each arrangement. The conductive rod <NUM> provides a charge return path, such that charges from the environment can flow back to the sensors by coupling with a human hand operating the conductive rod. The same effect may be achieved through the use of a grounded conductive encapsulant.

<FIG> shows, on the left, an intact state (top) and a damaged state (bottom, showing three cuts) of a communication medium of sixteen sensor nodes with respective integrated sensors, arranged in a grid formation. Shown on the right are corresponding representations of pressure detected by each sensor node in the intact state (top) and the damaged state (bottom), respectively. As discussed above in relation to <FIG>, the conductive fabric <NUM> or the mesh/planar conductor portion <NUM>' provides redundant signal paths, allowing communication of the sensor nodes to remain unaffected even when the conductive fabric <NUM> or the mesh/planar conductor portion <NUM>' is in the damaged state. In comparison, communication capability of an array of <NUM> sensors placed on a conventionally implemented row and column traces is significantly impaired when the traces are in a similar damaged state of three cuts (see <FIG>).

The temporal precision of a sensor node <NUM> is limited mainly by the duration of a single voltage pulse. As more sensor nodes <NUM> are added to the array, the capacitance of the electrical conductor through which the pulses propagate also increases. The increased capacitance results in a reduced phase margin of the op-amp feedback loop (i.e., the summing circuit <NUM>) and causes ringing in the output (<FIG>). The ringing can be reduced by increasing the feedback capacitance CF (i.e., the capacitance of the capacitor <NUM>, <FIG>) to improve stability. However, the pulse width will increase as a result (<FIG>). A SPICE simulation (Cadence® Spectre®) is used to determine how the pulse width changes with an increasing number of sensor nodes. The output of each sensor node <NUM> is modelled as a voltage source with a square wave. The edges of the waveform are high pass filtered to obtain the waveform of the voltage pulse (<FIG>). A transient simulation is run for N = <NUM> to <NUM>. For each N, the value of CF is swept to find the minimum CF that has acceptably low levels of ringing where the overshoot does not exceed quantization threshold set at <NUM>% of pulse amplitude. Finally, Fsample is obtained as the reciprocal of the resultant pulse width, taken to be the length of time in which the voltage remains above quantization threshold.

As discussed above, the signatures associated with the sensor nodes are designed to be sent independently (asynchronously) with a high probability of correlation at the respective filters. Each pulse signature consists of W voltage pulses spaced apart at specific time instancesτ = {τ<NUM>, τ<NUM>. At the receiving end, pulses are received at time instances τ' = {τ<NUM>', τ<NUM>'. The receiver finds the intersection τ = (τ∩τ') where the cardinality |T | denotes the correlation strength. If the correlation strength exceeds a predefined threshold (i.e., the correlation threshold value), a signature is deemed to have been correlated by the respective filter.

An ideal set of pulse signatures is one that has minimal autocorrelation (correlation between a particular signature and its time-shifted versions) and cross-correlation (correlation between a particular signature and other signatures in the set). There should also be enough unique signatures in the set to identify all sensor nodes in the array (cardinality). As discussed above, a family of pulse signatures may be characterized by the same <NUM> parameters:.

For a pulse signature with a signature duration (Ts) of <NUM> and a pulse duration (Tp) of <NUM> ns: <MAT>.

Parameters ω and λ are closely related to the error performance of the receiver. Under ideal conditions, all ω voltage pulses of the target signature should be successfully correlated, and thus ω is the maximum correlation. λ is the maximum cross-correlation allowed between signatures of the same family. If N non-target signatures overlap with the target signature, the amount of interference could be as high as N × λ. Error performance will thus degrade if N × λ is much larger than ω.

The number of unique pulse signatures must match that of the sensor nodes. To accommodate for thousands of the sensor nodes, the pulse signatures may be configured to have λ = <NUM> such that the number of signatures (C) satisfies: <MAT>.

Therefore, with F = <NUM> and ω = <NUM>, the array can accommodate up to <NUM>,<NUM> sensor nodes, which should be sufficient in most cases for whole body robot sensor skins. As described above, the pulse signatures are electrical and can be either positive or negative (i.e., have positive or negative pulses), which allows each signature to take on several variants. For instance, two signatures of the same pulse positions and opposite pulse polarities may be considered to be two states or variants of a single signature, for indicating a binary '<NUM>' and a binary '<NUM>', respectively. With such a consideration, a single signature may be used by a FA sensor to indicate, using the two states or variants of the signature, an increase and a decrease in pressure. This is not possible with Optical Code Divisional Multiple Access used in fibre optic communication, which requires complicated optical devices for signal generation and transmission.

Some advantages of the present disclosure are discussed below.

Stimuli of a stimulus event can be sparse or dense. To achieve an accurate spatiotemporal representation of the stimulus event (e.g. vision, hearing, taste, touch, smell, etc.), sensory signals must be generated and transmitted with a high temporal resolution. The apparatus <NUM> is well suited for such tasks. Firstly, sensory signals generated by the respective sensors <NUM> are transmitted by the respective sensor nodes <NUM> in the form of respective unique pulse signatures <NUM> through the conductive fabric <NUM>. The process does not require any complex circuitry for digitisation. Further, the sensor nodes <NUM> do not require any implementation of synchronization or collision sensing. Further, no common signal ground is needed. The sensor nodes <NUM> can transmit respective unique pulse signatures <NUM> independently at any instance with minimal communication overhead. Contrary to conventional frame-based sensors where readings are periodically polled by a controller, each sensor node <NUM> transmits the respective signature <NUM> only when a stimulus is detected by the respective sensor <NUM>.

The temporal resolution achievable by the receiver <NUM> is limited mainly by a response time of the edge detection circuit, which, depending on implementation, can be less than a few nanoseconds and be well above the sampling period of any existing sensor arrays (e.g. tactile sensor arrays). The apparatus <NUM> is able to resolve signatures <NUM> transmitted microseconds apart. The receiver <NUM> can also be configured to activate some of its components (e.g., the filters <NUM>) only when its edge detection circuit detects an edge in the incoming signal. This configuration will greatly reduce the power consumption of the receiver <NUM>, particularly where the stimuli of the stimulus event are sparse.

Moreover, signal communication via the conductive fabric <NUM> or the mesh/planar conductor portion <NUM>' is highly robust to damages such as tears. As such, sensor nodes <NUM> may be flexibly arranged with respect to the conductive fabric <NUM> or the mesh/planar conductor portion <NUM>' without increasing wiring complexity. Such arrangements can be considered to provide redundancy signal conducting paths for each sensor node <NUM>. Therefore, density and distribution of the sensor nodes <NUM> can be flexibly varied to suit various application requirements.

Where the communication medium <NUM> is implemented to include thousands of sensor nodes <NUM> each associated with a unique pulse signature <NUM>, the apparatus <NUM> can achieve a bit error rates (BER) of around <NUM> (<NUM>%) even with the sensor nodes <NUM> transmitting the respective pulse signature <NUM> within <NUM> millisecond from one another. Where the stimuli are sparse, an even lower BER is can be achieved. The apparatus <NUM> can achieve a high scalability, potentially up to millions of sensor nodes <NUM>.

In addition, voltage pulses are less susceptible to low frequency interferences (e.g. from a source of AC power noise). They can also be detected without the need for expensive high-resolution ADCs. Voltage pulses have a much shorter duration compared to a chip in CDMA. This is equivalent to having a relatively high spread factor, achieving a significantly higher capacity than possible with CDMA.

The pulses are bipolar and therefore the signatures <NUM> can be asynchronously transmitted. Conversely, Optical CDMA pulses are unipolar and thus are not decodable without the use of additional synchronization signals/protocols. In addition, Optical CDMA uses fibre optics, which are not as damage resistant in terms of signal conducting path, and requires dedicated electro-optical components.

The apparatus <NUM> can achieve a high scalability and can be implemented for ultra-fast somatosensory applications. It can also maintain a near-constant ultra-high precision spatiotemporal pattern of stimulation from the sensors to the receiver and can support even tens of thousands of sensors. The conductive fabric requires minimal wiring complexity, can provide high degrees of flexibility in sensor node placement, and provides robust signal conducting paths for the sensor nodes.

With the above advantages, the apparatus <NUM> is particularly useful in next generation Artificial Intelligence (AI) driven-robots and autonomous systems in industries such as hospitals and home care, where robots may be deployed in rapidly changing complex environments. It will also be useful in many other applications involving human-machine interfaces, such as wearable assistive exo-skeleton suits requiring rapid tactile environment feedback.

Some alternative arrangements of the present disclosures are discussed below.

In an alternative embodiment, the unique pulse signature of one of the sensor nodes has a first signature duration and the unique pulse signature of another of the sensor nodes has a second signature duration different from the first signature duration. That is, the unique pulse signatures may have different numbers of pulses. The unique pulse signatures may have different signature durations. The unique pulse signatures may have different pulse durations. As long as the signatures are unique, any suitable arrangements may be adopted.

In other embodiments, the sensor nodes <NUM> can be realised in any suitable form of specialized analog or digital circuits.

The communication medium <NUM> may be adapted to cover at least a portion of, for example, a vehicle or a human.

The stimulus event may be an optical event, temperature, pressure or stimuli associated with electromagnetic waves. The stimulus event may relate to chemical, smell, audio, vibratory stimulation. The stimulus event may be a combination of different stimulus types and can include <NUM>nd order (processed) signals such as friction, slippage, wetness, hardness, etc. Indeed, the triggering event may be non-stimulus related. A skilled person would also appreciate that each sensor node can be associated with any type of sensor, provided that the sensor node is associated a signature for each possible state of detection of the sensory signal of the associated sensor.

The receiver <NUM> may be arranged local to the sensor nodes <NUM> of the receiver <NUM> may be arranged remote to the sensor nodes <NUM> and the transmission medium may be via any medium suitable for wireless transmission.

The sensors <NUM> may include tactile/pressure sensors of different sensitivities. They may also include different types of sensors, such as bio-mimetic tactile receptors, optical sensors including silicon electronics based ones, etc, acoustic sensors, piezo-electric sensors and other sensors that may or may not have neuro-morphic features. Sensors for the detection of electro-magnetic fields, humidity, surface textures, vibrations, acceleration, optical, temperature, chemical, shear, proximity/light, etc., may also be included.

The conductive medium may include at least one of a conductive fabric, a conductive bulk conductor, a conductive substrate, a conductive solid, a conductive gel, and a conductive fluid, provided that the transmission medium is able to conduct the signatures transmitted by the sensor nodes <NUM>. The conductive fluid (e.g., conductive liquid) or the conductive gel may be in-filled within micro-channels of, for example, a micro-fluidic device.

Each sensor node <NUM> may be associated with additional signatures to indicate states (e.g., operation, debug, battery level, error, debug, and modalities) of the respective sensor node <NUM>.

Claim 1:
A sensor-based communication apparatus (<NUM>) comprising:
a plurality of sensor nodes (<NUM>) associated with respective unique pulse signatures (<NUM>) and adapted to communicate with respective sensors (<NUM>),
wherein each sensor node of the plurality of sensor nodes (<NUM>) is configured to receive a corresponding sensory signal (113a) that is generated by a corresponding sensor in response to a respective stimulus (113b),
wherein said each sensor node (<NUM>) is configured, upon receipt of the corresponding sensory signal (113a), to transmit the associated unique pulse signature (<NUM>) independently and asynchronously through a transmission medium (<NUM>) shared by the sensor nodes (<NUM>), the unique pulse signatures (<NUM>) transmitted by the sensor nodes (<NUM>) being a representation of a stimulus event associated with the stimuli (113b) detected by the corresponding sensors (<NUM>),
wherein each of the sensor nodes (<NUM>) is associated with a given unique pulse signature (<NUM>) comprising a plurality of pulses, wherein the interval between each possible combination of two pulses among said plurality of pulses represents an inter-pulse interval of said given pulse signature, and
wherein each inter-pulse interval of the unique pulse signature (<NUM>) of each of the sensor nodes (<NUM>) has a unique duration among the durations of all the inter-pulse intervals of the unique pulse signatures (<NUM>) of all of the sensor nodes (<NUM>).