Anesthetizing monitoring system, unit and method therefore

Abstract

The invention relates to a method (800) performed by the anesthetizing monitoring unit (110), the method comprising: controlling transmission (810) of a first plurality of stimuli signals (210) using a first set of stimuli signal characteristics, receiving (820) input data indicative of response signals (230) received in response to the transmitted stimuli signals, calculating (830) a trend (920) using the received input data, wherein the trend (920) indicates at least amplitude values of one or more response signals (230), estimating (840) an amplitude value of a response signal using the calculated trend (920).

Description

[0001] ANESTHETIZING MONITORING SYSTEM, UNIT AND METHOD THEREFORE

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to anesthetizing monitoring systems, in particular anesthetizing monitoring systems capable of measuring a level of block of a subject.

[0004] BACKGROUND

[0005] In hospitals around the world, patients are administered muscle relaxants also called neuromuscular blocking agents, NMBAs, which inhibit neuromuscular transmission. These relaxant agents decrease muscle tension and suppress reflex contractions. The different agents of NMBAs have different onset and durations but normally they have to be administered repeatedly, and the dose needs to be titrated appropriately, to maintain a desired concentration level or blood concentration throughout a surgical procedure.

[0006] It is desirable that the effects of the drugs completely dissipate once the surgical procedure is complete and the patient is in recovery, e.g. so that patients are able to breathe on their own (independently and spontaneously). Reversal drugs (e.g. anticholinesterases or sugammadex) can be administered to speed-up recovery from muscle relaxants but must also be administered in a controlled manner over time as reversal drugs can slow the heart to dangerous levels (bradycardia), and can have a host of other unpleasant side effects.

[0007] Neuromuscular monitoring systems using evoked electromyography, EMG, is nowadays regarded as the new gold standard for measuring the degree of neuromuscular function or, equivalently, the depth of muscular block. Evoked EMG involves sending a stimuli signal to stimulating electrodes positioned on the patient’s body and monitoring the response signal from receiving electrodes also positioned on the patient’s body.

[0008] A drawback of neuromuscular monitoring systems based on other measuring technologies is that stimulation and measurement is based on very old science, where the responses were detected by visually observing twitches in the patient's hand. In addition, response signals and hence the assessment of the patient is very much dependent on the device and the sensing technology that is used for the measurement. EMG measures the compound evoked potential over the innervated muscle. Measures such as acceleromyography, AMG, kinemyography KMG and mechanomyography MMG measures physical features of the actual movement of the hand. A further drawback is that conventional solutions cannot handle situations where administration of the NMBAs are initiated before monitoring is started.

[0009] Thus, there is a need for an improved system, unit, and method for anesthetizing monitoring.

[0010] OBJECTS OF THE INVENTION

[0011] An objective of embodiments of the present invention is to provide a solution which mitigates or solves the drawbacks described above.

[0012] SUMMARY OF THE INVENTION

[0013] The above objective is achieved by the subject matter described herein. Further advantageous implementation forms of the invention are described herein. The invention is set out in the appended claims. The scope of the invention is defined by the claims, which are incorporated into this section by reference.

[0014] According to a first aspect of the invention, the above-mentioned objective is achieved by a method performed by the anesthetizing monitoring unit, the method comprising: controlling transmission of a first plurality of stimuli signals using a first set of stimuli signal characteristics, receiving input data indicative of response signals received in response to the transmitted stimuli signals, calculating a trend using the received input data, wherein the trend indicates at least amplitude values of one or more response signals, estimating an amplitude value of a response signal using the calculated trend.

[0015] In one embodiment, the amplitude value is estimated for a baseline value, wherein the baseline value represents an amplitude of a response signal before the subject has been administered any drugs.

[0016] In one embodiment, the amplitude value is estimated for a response signal for which no signal could be detected.

[0017] According to a second aspect of the invention, the above-mentioned objective is achieved by an anesthetizing monitoring unit configured to measure a level-of-block of a subject, the anesthetizing monitoring unit comprising: an input port, an output port, and processing circuitry being configured to perform the method according to the first aspect.

[0018] According to a third aspect of the invention, the above-mentioned objective is achieved by an anesthetizing monitoring system configured to measure a level-of-block of a subject, the anesthetizing monitoring system comprising: an anesthetizing monitoring unit according to the second aspect, stimulating electrodes electrically coupled to the output port and being configured to receive a stimuli signal from the output port and deliver the stimuli signal to the subject, receiving electrodes electrically coupled to the input port and being configured to obtain a response signal, received in response to the stimuli signal, from the subject, the anesthetizing monitoring unit being configured to perform the method according to the first aspect.

[0019] According to a fourth aspect of the invention, the above-mentioned objective is achieved by a computer program is provided comprising computer-executable instructions for causing an anesthetizing monitoring unit, when the computer-executable instructions are executed on a processing unit comprised in the anesthetizing monitoring unit, to perform the method according to the first aspect.

[0020] According to a fifth aspect of the invention, the above-mentioned objective is achieved by a computer program product comprising a computer-readable storage medium, the computer- readable storage medium having the computer program according to the fourth aspect embodied therein.

[0021] A more complete understanding of embodiments of the invention will be afforded to those skilled in the art, as well as a realization of additional advantages thereof, by a consideration of the following detailed description of one or more embodiments. Reference will be made to the appended sheets of drawings that will first be described briefly

[0022] BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Fig. 1 shows an anesthetizing monitoring system according to one or more embodiments of the present invention.

[0024] Fig. 2A-B illustrates signal diagrams of stimuli and response signals according to one or more embodiments of the present invention.

[0025] Fig. 3A-B illustrates stimuli and response signal characteristics according to one or more embodiments of the present disclosure.

[0026] Fig. 4 illustrates details of an anesthetizing monitoring unit according to one or more embodiments of the present invention.

[0027] Fig. 5 illustrates a concept of the disclosure according to one or more embodiments of the present disclosure. Fig. 6 illustrates a flowchart of a method according to one or more embodiments of the present disclosure.

[0028] Fig. 7 illustrates a further concept of the disclosure according to one or more embodiments of the present disclosure.

[0029] Fig. 8 shows a block diagram of a method according to one or more embodiments of the present invention.

[0030] Fig. 9 illustrates calculation of a trend of amplitudes of the response signals according to one or more embodiments.

[0031] Fig. 10 illustrates an example of calculating of a trend of amplitudes of the response signal according to one or more embodiments.

[0032] Fig. 11 illustrates a further concept of the disclosure according to one or more embodiments of the present disclosure.

[0033] Fig. 12 illustrates a flowchart of a method according to one or more embodiments of the present disclosure.

[0034] Fig. 13 illustrates rendered representations according to one or more embodiments of the present disclosure.

[0035] Fig. 14 illustrates a flowchart of a method according to one or more embodiments of the present disclosure.

[0036] Fig. 15 illustrates a further concept of the disclosure according to one or more embodiments of the present disclosure.

[0037] Fig. 16 illustrates details of determining an LOB value according to one or more embodiments.

[0038] Fig. 17 illustrates a physiological model according to one or more embodiments.

[0039] Fig. 18 illustrates determining LOB value and adaption of stimuli signal characteristics according to one or more embodiments.

[0040] Fig. 19 illustrates a flowchart of a method according to one or more embodiments of the present disclosure.

[0041] Fig. 20 illustrates an anesthetizing monitoring unit according to one or more embodiments of the present invention.

[0042] Fig. 21 illustrates further rendered representations of an LOB current and historic LOB values according to one or more embodiments of the present disclosure. Fig. 22 illustrates further rendered representations of a trend of LOB values according to one or more embodiments of the present disclosure.

[0043] A more complete understanding of embodiments of the invention will be afforded to those skilled in the art, as well as a realization of additional advantages thereof, by a consideration of the following detailed description of one or more embodiments. It should be appreciated that like reference numerals are used to identify like elements illustrated in one or more of the figures.

[0044] DETAILED DESCRIPTION

[0045] The present disclosure relates to monitoring of muscular block following administration of a drug which inhibit neuromuscular transmission and / or its reversal agent. The different agents of NMBAs have different onset and durations but normally they have an effect that lasts only for a certain number of minutes, so they may have to be administered repeatedly throughout a surgical procedure.

[0046] The present disclosure addresses the problem of safer administration of drugs by resolving “missing responses” by predicting characteristics of historical, current, or future response signals. This allows for estimating LOB based on initial or baseline measures, when measurements are initiated after a drug has been administered. In other words, it is possible to obtain an estimate of an initial measurement also for patients already blocked. E.g., when performing so called T 1 LOB measures. This further allows to obtain level of block readings even when the signal quality is very low.

[0047] In other words, the present disclosure has the advantage of reducing complexity and increasing quality and increasing safety when administrating muscle relaxants by supporting the user, typically an anesthesiologist, to control the level of block.

[0048] An “or” in this description and the corresponding claims is to be understood as a mathematical OR which covers ’’and” and “or”, and is not to be understand as an XOR (exclusive OR). The indefinite article “a” in this disclosure and claims is not limited to “one” and can also be understood as “one or more,” i.e. , plural.

[0049] The term anesthetizing monitoring unit signifies herein a unit comprising processing circuitry, such as a processor and coupled memory, adapted for or suitable to be used in a hospital environment, e.g. when performing or recovering from surgery. Examples may include a dedicated computer system, an Electronic Control Unit, a server, a tablet, a smart watch, or a smartphone. The term stimuli signal signifies herein a signal delivered to an anesthetized patient or subject to stimulate a motor nerve. The stimuli signal may e.g. be in the form of a pulse in a pulse wave or pulse train pulse or a plurality of pulse wave or pulse train pulses having a determined voltage or current amplitude. The stimuli signal is typically delivered to stimulating electrodes attached to an anesthetized patient. The stimuli signal may e.g., be a train of four, TOF, signal.

[0050] The term response signal signifies herein a signal received in response to a respective transmitted stimuli signal. The response signal may e.g. be in the form of a sinusoidal signal, a pulse wave or pulse train pulse or a plurality of pulse wave or pulse train pulses having voltage and / or current amplitude. The response signal is typically obtained from receiving electrodes 121 attached to an anesthetized patient 130. The response signal may e.g., be an evoked electromyography, EMG, response signal.

[0051] In one example, a subject having been administered a muscle relaxant agent and the method herein includes stimulating a motor nerve with the stimuli signal. After each stimulus of the motor nerve, the muscle response in the muscle(s) innervated by the stimulated motor nerve is recorded as a response signal SResponse, e.g. to provide an assessment of neuromuscular function or level of block, LOB, in the subject. Each stimuli signal is sufficient to cause an evoked muscle response signal under normal physiological conditions. As muscle relaxants are administered to a subject, the amplitude of the evoked muscle response signal decreases. The amplitude typically decreases relative to historical or previously detected response signals or is decreased or reduced to a level where no response signal amplitude can be detected, as the drug takes effect.

[0052] The term “configured to” may be used interchangeably with “adapted to” or “operative to” in the disclosure herein.

[0053] The term “memory” may be used interchangeably with “computer readable medium” or “non- transitory computer readable medium” in the disclosure herein.

[0054] Provided in the present disclosure are systems, units, and methods for measuring and / or rendering / displaying LOB, e.g. by monitoring neuromuscular function or block of muscles in patients being administered muscle relaxants such as a neuromuscular blocking agent such as a depolarizing agent and / or a non-depolarizing agent.

[0055] Fig. 1 shows an anesthetizing monitoring system 100 according to one or more embodiments of the present invention. The anesthetizing monitoring system 100 may comprise an anesthetizing monitoring unit 110 provided with an input port 111 and an output port 112 according to embodiments described herein. In one or more embodiments the anesthetizing monitoring unit 110 may further comprise a display 113 communicatively coupled to processing circuitry and being configured to receive a display signal indicative of rendered objects, such as text or graphical user input objects and to display the received signal as objects, such as text or graphical user input objects. Examples of rendered objects are further described in relation to Fig. 13.

[0056] The anesthetizing monitoring system 100 may further comprise stimulating electrodes 122 configured to be electrically couplable to the output port 112 and being configured to receive a stimuli signal Sstimuii from the output port 112 and deliver the stimuli signal Sstimuii to the anesthetized patient / subject 130 via the stimulating electrodes 122. The stimuli signal may e.g., be a TOF signal. The anesthetizing monitoring system 100 may further comprise receiving electrodes 121 configured to be electrically couplable to the input port 111 and being configured to obtain a response signal SResponse, in response to the stimuli signal Sstimuii, obtained from the anesthetized patient 130.

[0057] It is understood that the stimulating electrodes 122 and the receiving electrodes 121 are attached to the skin of the subject / patient 130 as indicated in Fig. 1.

[0058] In one embodiment, an anesthetizing monitoring system 100 is provided and is configured to measure a level-of-block of a subject. The anesthetizing monitoring unit 100 comprises:

[0059] An anesthetizing monitoring unit 110, further described in relation to Fig. 4.

[0060] Stimulating electrodes 122 electrically coupled to an output port 112 of the anesthetizing monitoring unit 110 and being configured to receive a stimuli signal from the output port 112 and deliver the stimuli signal to the subject 130, typically at predetermined positions.

[0061] Receiving electrodes 121 electrically coupled to an input port 111 of the anesthetizing monitoring unit 110 and being configured to obtain a response signal, received in response to the stimuli signal, from the subject 130. The anesthetizing monitoring system is configured to perform any of the methods described herein.

[0062] Fig. 2A illustrates a signal diagram of stimuli signals according to one or more embodiments of the present invention. Current amplitude (I) is shown on the vertical axis of the diagram and time (T) is shown on the horizontal axis of the diagram. It is understood that the amplitude could also signify voltage and a similar diagram could be constructed showing voltage (II) on the vertical axis of the diagram. It is further understood that, even though the signal is illustrated as four pulses, or train of four TOF, the characteristics of the signal may vary according to a current set of stimuli signal characteristics used, without departing from the present disclosure. Examples of stimuli signal characteristics is pulse count, or a number of pulses, comprised in the stimuli signals, pulse frequency f of pulses grouped in each stimuli signal, pulse shape of pulses in the stimuli signal, duty cycle of pulses in the stimuli signal, duration of the of the stimuli signal, separation in time of multiple pluralities of stimuli signals 210, 220 etc.

[0063] Starting at a first time instant Tstimuii_starti, a first plurality of stimuli signals 210 are transmitted using the output port 112 of the anesthetizing monitoring unit 110. The first plurality of stimuli signals 210 uses a first set of stimuli signal characteristics, e.g., a pulse train of four pulses or Train of Four, TOF.

[0064] The pulse characteristics may comprise e.g., a pulse count indicating a number of subsequent pulses, a pulse frequency f, a pulse amplitude, duration and separation between multiple pluralities of stimuli signals Tseparation As mentioned, stimuli signals may e.g., be a pulse train, such as a train of four, TOF, signal.

[0065] The first plurality of stimuli signals 210 have duration of Tstimuin from the first time instant Tstimuii_starti to a second time instant Tstimuii_endi . As described further in relation to Fig. 1 , the first plurality of stimuli signals 210 is delivered to the anesthetized patient / subject 130 by stimulating electrodes 122 attached to the anesthetized patient 130.

[0066] The first plurality of stimuli signals 210 may comprise a pulse train, or a plurality of pulse trains, also referred to herein as a repeated pulse train.

[0067] Starting at a third time instant Tstimuii_start2, a second plurality of stimuli signals 220 are transmitted using the output port 112 of the anesthetizing monitoring unit 110. The second plurality of stimuli signals 220 uses a second set of stimuli signal characteristics.

[0068] The second plurality of stimuli signals 220 have duration of Tstimuii2 from a third time instant Tstimuii_start2 to a fourth time instant Tstimuii_end2. The duration Tstimuii2 Of the second plurality of stimuli signals 220 may be the same as the duration of the first plurality of stimuli signals 210 or different without departing from the present disclosure. The second plurality of stimuli signals 220 may in one example be transmitted using different characteristics, e.g., having a lower amplitude.

[0069] As described further in relation to Fig. 1 , the second plurality of stimuli signals 220 is delivered to the anesthetized patient / subject 130 by stimulating electrodes 122 attached to the anesthetized patient 130.

[0070] Stimuli signals 220 are further described in relation to Fig. 3A.

[0071] Fig. 2B illustrates a signal diagram of response signals according to one or more embodiments of the present invention. Voltage amplitude (II) of the response signal is shown on the vertical axis of the diagram and time (T) is shown on the horizontal axis of the diagram. It is understood that the amplitude could also signify current, and a similar diagram could be constructed showing electrical current (I) on the vertical axis of the diagram.

[0072] As mentioned in relation to Fig. 2A, the shape of the response signal is shown as a sinusoidal signal for illustration purposes, but it is understood that the shape and characteristics of the response signal may vary without departing from the present disclosure.

[0073] After transmission of the first plurality of stimuli signals 210, a first plurality of response signals 230 is received in response to the transmitted stimuli signals 210. The stimuli signals 210 are shown in Fig. 2A and the response signals 230 are shown in Fig. 2B.

[0074] The first plurality of response signals 230 may be in the form of a pulses SResponse_i SResponse_4 having amplitude or having a shape similar to a sinusoid signal, with the amplitude typically being measured between the positive and negative peak of the sinusoid signal.

[0075] The first plurality of response signals 230 are typically time synchronized to the respective stimuli signals, and typically detected within a time window. The time window used for measuring the response signals may be multiples larger than the duration of the respective stimuli signal. The first plurality of response signals 230 have a duration of TResponsei, which typically have a larger duration than that of the of the stimuli signal Tstimuin .

[0076] In one example, when using a train of four, TOF, pulse train the duration of the stimuli signal Tstimuiii may e.g., be 300 ps and the duration of response signals TResponsei, is approximately 15-20 ms. To account for variations in delay, measurements of the response signal may be performed in 100 ms.

[0077] As described further in relation to Fig. 1 , the first plurality of response signals 230 is obtained from the anesthetized patient 130 by receiving electrodes 121 attached to the anesthetized patient 130. The first plurality of response signals 230 is received using the input port 111 of the anesthetizing monitoring unit 110.

[0078] After transmission of the second plurality of stimuli signals 220, a second plurality of response signals 240 is received in response to the transmitted stimuli signals 220. The stimuli signals 220 are shown in Fig. 2A and the response signals 240 are shown in Fig. 2B.

[0079] The second plurality of response signals 240 may be in the form of a pulses SResponse_i SResPonse_4 having response signal characteristics such as amplitude or a single cycle of a sinusoid signal, also with the amplitude typically being measured between the positive and negative peak of the sinusoid signal. The second plurality of response signals 240 are typically time synchronized to the respective stimuli signals 220, and typically detected within a time window. The second plurality of response signals 240 have a duration of TResponse2, which typically have a larger duration than that of the of the stimuli signal Tstimuii2.ln one example, when using a train of four, TOF, the duration of the stimuli signal Tstimuin may be e.g., 300 ps and the duration of response signals Tpesponsei , is approximately 15-20 ms. To account for variations in delay, measurements of the response signal may be performed in 100 ms.

[0080] As described further in relation to Fig. 1 , the second plurality of response signals 240 is obtained from the anesthetized patient 130 by receiving electrodes 121 attached to the anesthetized patient 130. The first plurality of response signals 230 is received using the input port 111 of the anesthetizing monitoring unit 110.

[0081] In one example of the present disclosure, the first plurality of response signals 230 is analyzed and used to adjust / adapt stimuli signal characteristics for the second plurality of stimuli signals 220.

[0082] Fig. 3A illustrates stimuli signal characteristics according to one or more embodiments of the present disclosure.

[0083] As shown in relation to Fig. 2A, the transmitted stimuli signal has a duration Tstimuii and typically comprises a plurality of stimuli signals Sstimuin to Sstimuii_4 it is understood that any number of pulses having any suitable shape may be used without departing from the present disclosure.

[0084] In the example shown in Fig. 3A, a pulse train with four pulses, TOF, is shown. In the example, the plurality of stimuli signals has stimuli signal characteristics comprising a pulse count, PC, of four. In a further example, the stimuli signal characteristics comprises duty cycle or a ratio of the pulse width to the pulse period. In the example shown in fig 3A, the duty cycle is 50%. In the example shown in Fig. 3A, the stimuli signal characteristics comprises a pulse frequency f, which means that pulses are separated 1 / f in time. In the example shown in Fig. 3A, the stimuli signal characteristics comprises signal amplitude, SAS, e.g., electrical current amplitude. As mentioned previously, the stimuli signal characteristics may further comprise an electrical voltage amplitude.

[0085] Fig. 3B illustrates response signal characteristics according to one or more embodiments of the present disclosure.

[0086] As shown in relation to Fig. 2B, the received response signal has response signal characteristics, such as a duration TResponse and typically comprises a plurality of sinusoidal pulses SResPonse_1 tO SResPonse_4- In the example shown in Fig. 3B, a response signal with four pulses or peaks in a sinusoidal signal, resulting from the train of four (TOF) signal illustrated in Fig. 3A, is shown. In the example, the plurality of response signals has response signal characteristics comprising a pulse count, PC, of four. In the example shown in Fig. 3B, the response signal characteristics comprises signal amplitude, SAR, e.g., voltage amplitude. The amplitude is typically measured between the positive and negative “peak” of the sinusoidal signal. As mentioned previously, the response signal characteristics may additionally, or alternatively, comprise an electrical current amplitude in Ampere.

[0087] The response signal characteristics may comprise any suitable signal measures known in the art, such as train of four count, TOFC, train of four ratio, TOFR, and baseline first pulse to current first pulse, T1. The TOFC measure is the number of detected muscle responses resulting from a TOF stimulation. The TOFR is a measure in percent between amplitude of a first pulse in a detected response signal and amplitude the last pulse, i.e., a ratio between amplitudes of a first and fourth pulse of detected muscle responses resulting from a TOF stimulation. T1 is a measure of a ration between amplitude of a first pulse in a baseline or initial response signal and amplitude a first pulse in the most recent response, i.e., a ratio between amplitudes of a baseline pulse and a first pulse of the most recent detected muscle responses resulting from a TOF stimulation.

[0088] Fig. 4 illustrates details of an anesthetizing monitoring unit 110 according to one or more embodiments of the present invention. The anesthetizing monitoring unit 110 comprises processing circuitry 103. The processing circuitry 103 may comprise a processor 102 communicatively coupled to a memory 106, said memory 106 comprising instructions executable by said processor, whereby said anesthetizing monitoring unit 110 is operative to perform the method of any of the embodiments described herein.

[0089] The processing circuitry 103 may in one optional embodiment be communicatively coupled to a communication interface 101 , e.g. comprising one or more transceivers 104. The communication interface 101 may be operative to receive information, such as a data packet, from the processor 102 and generate a wireless signal S for a wireless communication network or to receive the wireless signal S for a wireless communication network. Alternatively, a wired signal for a wired communication network is generated. The communication interface 101 may further be operative to demodulate and / or decode the wireless / wired signal to a data packet and send to the processor 102. Further, the anesthetizing monitoring unit 110 may further comprise one or more optional antennas 108, as shown in Fig. 5. The antenna / s 108 is / are coupled to the transceiver / s 104 and is / are configured to transmit / emit or receive wireless signals S for a wireless communication network, e.g. transmit a data packet included or comprised in the wireless signal S. The data packet may comprise a representation of the stimuli signals, the response signals, or any other data. The processor and / or a processor unit 102 may be, e.g. processing circuitry and / or a central processing unit and / or processor modules and / or multiple processors configured to cooperate with each-other. The memory 106 may comprise of essentially any suitable memory, such as a ROM (Read-Only Memory), a PROM (Programmable Read-Only Memory), an EPROM (Erasable PROM), a Flash memory, an EEPROM (Electrically Erasable PROM), or a hard disk drive. The communication interface 101 may be configured to send or receive data to other nodes such as servers or other anesthetizing monitoring units. E.g. transmitting or receiving the stimuli signals and / or the response signals.

[0090] The processing circuitry 103 may in one embodiment be communicatively coupled to a measurement interface 105. The measurement interface 105 is further coupled or communicatively coupled to the input port 111 and the output port 112. The measurement interface 105 is configured to transmit the stimuli signal Sstimuii in response to a control signal received from the processing circuitry 103. The control signal may e.g. comprise properties of the stimuli signal Sstimuii, such as the amplitude. The measurement interface 105 is further configured to receive the response signal SResponse, detecting properties / characteristics of the response signal SResponse such as the amplitude, and send the properties of the response signal SResponse to the processing circuitry 103. The properties of the response signal SResponse may include one or more amplitude values.

[0091] In one or more embodiments, the anesthetizing monitoring unit 110 may further comprise an input device 114 configured to receive input or indications from a user and send a user-input signal indicative of the user input or indications to the processing circuitry 103.

[0092] In one or more embodiments the anesthetizing monitoring unit 110 may further comprise a display 113 communicatively coupled to the processing circuitry 103 and being configured to receive a display signal indicative of rendered objects, such as text or graphical user input objects, from the processing circuitry 103 and to display the received signal as objects, such as text or graphical user input objects. Examples of rendered objects are further described in relation to Fig. 13.

[0093] In one embodiment, the display is integrated with the user input device and is configured to receive a display signal indicative of rendered objects, such as text or graphical user input objects, from the processing circuitry 103 and to display the received signal as objects, such as text or graphical user input objects, and / or configured to receive input or indications from a user and send a user-input signal indicative of the user input or indications to the processing circuitry 103.

[0094] In embodiments, the processing circuitry 103 is further communicatively coupled to the input device and / or the display.

[0095] According to one aspect of the present disclosure, the anesthetizing monitoring unit 110 may automatically switch between a normal operational mode and a Deep Block mode. In one example, the anesthetizing monitoring unit 110 switches from Train-Of-Four, TOF simulation to Post-Tetanic Count, PTC, type stimulation when the signal quality of the response signal is too low.

[0096] The quality of the signal may e.g., be quantified using measures such as TOFC, TOFR and T1.

[0097] Fig. 5 illustrates a concept of the disclosure according to one or more embodiments of the present disclosure.

[0098] The plurality of response signals SResponse_i to SResponse_N received in response to the transmitted stimuli signals are typically converted to a data representation as input data, e.g. using analog to digital conversion as further described herein.

[0099] According to one aspect of the present disclosure, an operational mode of the anesthetizing monitoring unit 110 is automatically selected.

[0100] With reference to Fig. 2A-B and Fig. 3A-B the concept is described below.

[0101] Transmission of a first plurality of stimuli signals 210 using a first set of stimuli signal characteristics is controlled. In one example, the first set of stimuli signal characteristics is indicative of a normal operational mode SSCNormai, e.g., using TOF stimulation.

[0102] Input data is received and is indicative of response signals 230 received in response to the transmitted stimuli signals, wherein the input data is at least indicative of response signal characteristics, such as pulse amplitude values of the response signals 230.

[0103] An aggregated amplitude value is calculated using the input data. The aggregated amplitude value may be calculated as a maximum value, as a geometric average value or as a weighted average value. The aggregated amplitude value may further be calculated as a TOF count value.

[0104] In one example, the highest amplitude value of a plurality of response signals resulting from a TOF stimulation is selected. An updated set of stimuli signal characteristics is then generated being indicative of a normal operational mode SSCNormai, if the aggregated amplitude value is equal to or above a predetermined amplitude threshold, or being indicative of a Deep Block mode SSCDB if the aggregated amplitude value is below the predetermined amplitude threshold. Transmission of a second plurality of stimuli signals 220 is then controlled using the updated set of stimuli signal characteristics.

[0105] In one example, the anesthetizing monitoring unit 110 is operating in the normal operational mode SSCNormai, and none of the response signals received in response to a TOF stimulation is above a first predetermined amplitude threshold. This could e.g., involve calculating an aggregated amplitude value in the form of a TOFC=0. Updated stimuli signal characteristics may then generated indicative of a Deep Block mode SSCDB, typically single pulse or PTC type stimulation.

[0106] In one example, the anesthetizing monitoring unit 110 is operating in the Deep Block mode SSCob, and at least one of the response signals received in response to stimulation is above a second predetermined threshold. Updated stimuli signal characteristics is then generated indicative of a normal operational mode SSCNormai, typically TOF type stimulation. In other words, returning to the normal operational mode.

[0107] Additionally, or alternatively, the set of stimuli signal characteristics indicative of a normal operational mode SSCNormai indicate a duration of the stimuli signal below three seconds and a pulse frequency of a pulse train below 3 Hz and / or wherein the set of stimuli signal characteristics indicative of a Deep Block mode SSCDB indicate a duration of the stimuli signal above three seconds and a pulse frequency of a pulse train above 25 Hz.

[0108] Additionally, or alternatively, the set of stimuli signal characteristics indicative of the normal operational mode SSCNormai is indicative of a Train-Of-Four, TOF, stimuli signal, wherein the set of stimuli signal characteristics indicative of a Deep Block mode SSCDB is indicative of a single pulse or post tetanic count, PTC, stimuli signal.

[0109] Fig. 6 illustrates a flowchart of a method according to one or more embodiments of the present disclosure. The method is performed by the anesthetizing monitoring unit 110 described herein. The method comprises:

[0110] Step 610: controlling transmission of a first plurality of stimuli signals 210 using a first set of stimuli signal characteristics.

[0111] In one example, the first set of stimuli signal characteristics is indicative of a TOF stimuli signal.

[0112] Step 620: receiving input data indicative of response signals 230 received in response to the first plurality of transmitted stimuli signals, wherein the input data is at least indicative of pulse amplitude values of the response signals 230. Response signals are further described in relation to Fig. 2B.

[0113] Step 630: calculating an aggregated amplitude value using the input data.

[0114] The aggregated amplitude value is indicative of quality of the response signals.

[0115] In one embodiment, calculating the aggregated amplitude value comprises determining a TOF count value, TOFC.

[0116] Step 640: generating an updated set of stimuli signal characteristics indicative of a normal operational mode if the aggregated amplitude value is equal to or above a predetermined amplitude threshold, or generating an updated set of stimuli signal characteristics indicative of a Deep Block mode if the aggregated amplitude value is below the predetermined amplitude threshold.

[0117] In one embodiment, the updated set of stimuli signal characteristics indicative of a normal operational mode is equal to the first plurality of stimuli signals, as described in relation to step 610. In this embodiment, the updated set of stimuli signal characteristics indicative of a Deep Block mode is indicate a of a single pulse operational mode.

[0118] In one non-limiting example, the updated set of stimuli signal characteristics indicative of a normal operational mode is indicative of a TOF, stimulation signal. In one further non-limiting example, the updated set of stimuli signal characteristics indicative of a Deep Block mode is indicative of a single pulse or single twitch.

[0119] Step 650: controlling transmission of a second plurality of stimuli signals 220 using the updated set of stimuli signal characteristics.

[0120] In one example, if the quality of the received signals is relatively low, e.g., TOFC =0, a single pulse is transmitted to verify that the patient is in a deep block state. This is advantageous as situations where a patient is quickly recovering and is subjected to PTC stimulation can be avoided, thereby saving the patient from pain or discomfort.

[0121] Optional Step 660: receiving second input data indicative of second response signal / s, where the response signals are received in response to the transmitted second plurality of stimuli signals of step 650. In one embodiment, the second input data is at least indicative of a second pulse amplitude value of the response signal / s.

[0122] In one non-limiting example, the second response signal / s received, is indicative of a single pulse. Optional Step 670: calculating a second aggregated amplitude value using the second input data. In one embodiment, calculating the second aggregated amplitude value comprises detecting a single pulse.

[0123] In one example, calculating a second aggregated amplitude value by detecting a pulse comprises detecting a positive edge of a pulse, detecting a negative edge of a pulse or detecting that an amplitude value of a received pulse is above the predetermined threshold. In other words, detecting that the second pulse amplitude value of the response signal / s is above the predetermined threshold value.

[0124] Optional Step 680: generating a second updated set of stimuli signal characteristics indicative of a normal operational mode if the second aggregated amplitude value is equal to or above the predetermined amplitude threshold, or generating the second updated set of stimuli signal characteristics indicative of a Deep Block mode if the second aggregated amplitude value is below the predetermined amplitude threshold.

[0125] In one embodiment, the second updated set of stimuli signal characteristics indicative of a normal operational mode is equal to the first plurality of stimuli signals, as described in relation to step 610. In this embodiment, the second updated set of stimuli signal characteristics is indicative of a Deep Block mode indicating a PTC operational mode, e.g., with a duration of the stimuli signal above three seconds and a pulse frequency of a pulse train above 25 Hz.

[0126] In one non-limiting example, the second updated set of stimuli signal characteristics, indicative of a normal operational mode, is indicative of a TOF, stimulation signal. In one further nonlimiting example, the updated set of stimuli signal characteristics, indicative of a Deep Block mode, is indicative of PTC stimulation, e.g., pulses with a frequency of 50 Hz and a duration of five seconds.

[0127] Optional Step 690: controlling transmission of a third plurality of stimuli signals using the updated set of stimuli signal characteristics.

[0128] In one example, the normal operational mode is resumed and a TOF stimulation signal is transmitted. The method may then be repeated or resumed at step 620.

[0129] In one further example, the Deep Block mode is repeated, and a PTC stimulation signal is transmitted. The method may then be repeated or resumed at step 680 or 690.

[0130] In one embodiment, the set of stimuli signal characteristics indicative of a normal operational mode indicate a duration of the stimuli signal below three seconds and a pulse frequency of a pulse train below 3 Hz, wherein the set of stimuli signal characteristics indicative of a PTC mode indicate a duration of the stimuli signal above three seconds and a pulse frequency of a pulse train above 25 Hz.

[0131] In one embodiment, the set of stimuli signal characteristics indicative of the normal operational mode is indicative of a Train-Of-Four, TOF, stimuli signal, wherein the set of stimuli signal characteristics indicative of a Deep Block mode is indicative of a single pulse or post tetanic count, PTC, stimuli signal.

[0132] Additionally, or alternatively, the steps 610-630 are repeated (a number) N times. Additionally, or alternatively, generating an updated set of stimuli signal characteristics indicative of a Deep Block mode is only performed if all N aggregated amplitude values are below the predetermined amplitude threshold.

[0133] In other words, the method continues with step 640 only if the aggregated amplitude value indicates Deep Block mode for N subsequent occasions.

[0134] In one example, a TOF stimuli signal is transmitted, but no response signal amplitudes can be detected, i.e., are below a threshold. A single pulse stimulation signal is then applied to the patient , e.g., via the first electrodes. A potential sequence may look like:

[0135] A series of TOF signals is transmitted to a patient. A patient response is detected in response to the series of TOF signals. Amplitudes is determined from the detected responses. The average value of the amplitudes is calculated.

[0136] If it is determined that the individual amplitude of any of the responses is above a first predetermined threshold or the average value of the responses is above a second predetermined threshold, the preceding step of applying a series of stimulation signals etc. is repeated 3 to a suitable plurality of number N times.

[0137] In one further example, a TOF stimuli signal is transmitted, but no response signal amplitudes can be detected, i.e., are below a threshold and / or TOFC=0. Only after repeated failure to detect response signal amplitudes above a threshold, a single pulse stimulation signal is applied to the patient , e.g., via the first electrodes.

[0138] This has the advantage of adapting the stimuli signal in situations where the patient is in deep block or when signal quality of the response signals is bad or not usable.

[0139] In one embodiment, a monitor 110 is programmed to conduct an automatic monitoring cycle, the automatic monitoring cycle including: applying a series of stimulation signals to a patient via the first electrodes, detecting patient response to the series of stimulation signals via the second electrodes, determining amplitudes from the detected responses, calculating the average value of the amplitudes and if the individual amplitude of any of the responses is above a predetermined threshold or the average value of the responses is above a second predetermined threshold, automatically repeating the preceding step of applying a series of stimulation signals, and otherwise, applying a single pulse stimulation signal to the patient via the first electrodes.

[0140] If the single pulse cannot be detected, a a post tetanic count, PTC is determined.

[0141] Additionally, or alternatively, the steps of applying the series of stimulation signals, detecting patient response, determining amplitudes from the detected responses calculating the average value of the amplitudes are repeated a plurality N times, and wherein applying a tetanic stimulation signal to the patient is only performed if one or more subsequent single pulses are below the predetermined threshold.

[0142] In one embodiment, a monitor 110 is programmed to conduct an automatic monitoring cycle, the automatic monitoring cycle including: applying a series of stimulation signals to a patient via first set of electrodes, detecting patient response to the series of stimulation signals via a second set of electrodes, and determining a train of four, TOF, count from the detected patient response; and if the TOF count is at or above a predetermined threshold, automatically repeating the preceding step of applying a series of stimulation signals, and if the TOF count is below the predetermined threshold, automatically entering into a Deep Block mode, applying a single stimulation via the first electrodes, detecting patient response to the stimulation signals via the second electrodes, determining amplitudes from the detected response, and if the detected amplitude is above a predetermined threshold, automatically repeating the step of applying a single stimulation three times to complete a TOF measurement, and if the amplitude is below the predetermined threshold, automatically applying a tetanic stimulation signal to the patient via the first electrodes and determining a post tetanic count ,PTC.

[0143] According to one further aspect of the disclosure, signal characteristics of historical, current, or future response signals are predicted RSC.

[0144] A drawback of conventional solutions is that if a response signal is not detected, a LOB of a subject cannot be determined. Particularly in some situations, the first / baseline plurality of response signals / initial response (e.g., initial / baseline TOF response) is not obtained before an anesthetic substance has been administered to a subject or patient. The amplitude value of such a first / baseline response may then not be used to determine LOB, e.g., in a T1 calculation method.

[0145] Thus, there is a need for an improved method of measuring LOB of a subject.

[0146] In the present disclosure the above-mentioned drawbacks are addressed by determining such a first / baseline value using a calculated trend.

[0147] This may e.g., be achieved by calculating a trend using received response signal signals, e.g., by calculating response signal amplitudes, SA. Calculating trends are further described in relation to Fig. 9-10.

[0148] Fig. 7 illustrates a further concept of the disclosure according to one or more embodiments of the present disclosure.

[0149] The plurality of response signals SResponse_i to SResponse_N received in response to the transmitted stimuli signals are typically converted to a data representation as input data.

[0150] Response signal characteristics RSC is then predicted for one or more response signals. In one embodiment the prediction is made using a calculated trend.

[0151] In one example, the trend is calculated by applying curve fitting to amplitudes within the same plurality of response signals, e.g. within the plurality 230 shown in relation to Fig. 2B.

[0152] In some situations, the first / baseline plurality of response signals / initial response (e.g., initial TOF response) is not obtained before an anesthetic substance has been administered to a subject or patient. The first / baseline plurality of response signals / initial response may then be determined using a calculated trend.

[0153] In one embodiment, an initial response / baseline response can then be predicted by using the calculated trend of amplitudes described above.

[0154] Prediction of amplitudes are further described in relation to Fig. 9-10.

[0155] Fig. 8 shows a block diagram of a method 800 according to one or more embodiments of the present invention. The method 800 is performed by the anesthetizing monitoring unit 110 described herein. The method comprises:

[0156] Step 810: controlling transmission of a first plurality of stimuli signals using a first set of stimuli signal characteristics. Transmission of stimuli signals is further described in relation to Fig. 2A and Fig. 3A. Step 820: receiving input data indicative of response signals received in response to the transmitted stimuli signals. Reception of response signals is further described in relation to Fig. 2B and Fig. 3B.

[0157] It is understood that the steps of 810 and 820 may be repeated any number of times to collect the input data without departing from the present disclosure. In other words, currently received input data may be combined with historically received input data without departing from the present disclosure.

[0158] Step 830 calculating a trend 920 using the received input data. In one embodiment, the trend 920 indicates at least amplitude values of one or more response signals 230. The term “calculating a trend” can be used interchangeably with “generating a trend” and denotes deriving a relation between time and characteristics of the input data, e.g., amplitude values of one or more response signals.

[0159] Calculation of trends 920 are further described in relation to Fig. 9 and Fig. 10.

[0160] Step 840: estimating an amplitude value of a response signal using the trend 920.

[0161] In one embodiment, the amplitude value is estimated for a baseline value 910. The baseline value 910 may represent an amplitude of a response signal before the subject has been administered any drugs. Estimating a baseline value 910 is further described in relation to Fig. 9 and Fig. 10.

[0162] In one example, the estimated amplitude value is used for a T1 calculation of muscular block or a LOB value.

[0163] In one embodiment, the amplitude value is estimated for a response signal for which no signal could be detected. Estimating missing amplitude value of a response signal is further described in relation to Fig. 9.

[0164] Fig. 9 illustrates calculation of a trend of amplitudes of the response signals according to one or more embodiments.

[0165] In one embodiment of the methods described herein, a trend is calculated by applying curve fitting to amplitude values A1-A4 within the same plurality of response signals, e.g. within the plurality 230 shown in relation to Fig. 2B. Curve fitting may e.g., be applied by fitting a curve 920 to amplitude values A1-A4 of a single plurality of response signals.

[0166] In Fig. 9, curve fitting using an exponential curve is shown for illustrative purposes. It is understood that any other curve fitting may method be used, e.g., regression, polynomial regression, or polynomial interpolation. Curve fitting may further include providing the received input data to a model or trained model to calculate a trend.

[0167] In the example in Fig. 9, the trend is calculated by relating amplitude values of the plurality of response signals to each other, e.g., by considering fade of the response signal. It is understood that any selection of amplitude values of the plurality of response signals may be related to each other without departing from the present disclosure.

[0168] Using the calculated trend or curve 920, an amplitude value RSC of a response signal may be estimated or predicted.

[0169] In one example, measurements are only initiated after the subject has been administered any drugs that affect neuromuscular transmission. Determination of a T1 measure can then not be performed, as the current response amplitude values cannot be related to a baseline value. The trend 920 can then be used to estimate or predict the baseline value 910, e.g., by extending the curve shown in Fig. 9 to a point in time before the subject was administered any drugs.

[0170] In one example, one of the pulses in the same plurality of response signals cannot be detected for some reason, e.g. pulse amplitude A3 cannot be detected. The missing amplitude value A3 may then be estimated using the calculated trend or curve 920, typically an amplitude value between A2 and A4, e.g., by determining the amplitude (vertical axis) from the diagram in Fig. 9 at a time when the pulse was expected.

[0171] Fig. 10 illustrates an example of calculating of a trend 920 of amplitudes A1-A8 of the response signal according to one or more embodiments.

[0172] In the example in Fig. 10, the trend is calculated by applying curve fitting to amplitudes A1-A8 selected from multiple pluralities of response signals Responsel , Response2. In particular, a first plurality of response signals / initial response / baseline response (e.g., initial TOF response) and any of the following plurality of response signals may be used.

[0173] In other words, the amplitudes A1-A8 selected from multiple pluralities of response signals may be aggregated to calculate the trend, e.g., by averaging amplitudes before applying curve fitting. Aggregating amplitudes may also include weighted averaging, where recently measured amplitude values are given a larger weight than older amplitude values.

[0174] In one embodiment, the method further comprises estimating a baseline value 910 using the calculated trend 920 of amplitudes A1-A8.

[0175] In a similar manner, a future point may be predicted 930 using the trend 920. It is understood that the baseline value 910 can then be used to determine an LOB value.

[0176] According to one further aspect of the disclosure, stimuli signals are adapted in response to at least response signal characteristics.

[0177] Conventional solutions typically use stimuli signals having fixed characteristics, e.g. using TOF stimulation with fixed pulse amplitude, fixed pulse frequency and fixed pulse count.

[0178] At least one drawback of such conventional solutions is that optimal stimulation is not achieved as a fixed stimulation pattern is not optimal for all levels of block.

[0179] Thus, there is a need for an improved method of measuring level of block of a subject.

[0180] Fig. 11 illustrates a further concept of the disclosure according to one or more embodiments of the present disclosure.

[0181] The plurality of response signals SResponse_i to SResponse_N received in response to the transmitted stimuli signals are typically converted to a data representation as input data. Further, historic stimuli signal characteristics SSC may optionally be used. Further, historic LOB values may optionally be used.

[0182] In brief, the present disclosure can be described as:

[0183] T ransmission of a first plurality of stimuli signals using a first set of stimuli signal characteristics is controlled by the monitor 110. Input data indicative of response signals 230 is received, via the receiving electrodes 121 , in response to the transmitted stimuli signals. An updated set of stimuli signal characteristics is then generated using the input data. Finally, transmission of a second plurality of stimuli signals 220 is controlled using the updated set of stimuli signal characteristics.

[0184] By constantly monitoring the characteristics of the response signals, an adapted and improved stimuli signal can be generated, thereby improving the quality of the next plurality of response signals.

[0185] Fig. 12 illustrates a flowchart of a method according to one or more embodiments of the present disclosure. The method is performed by the anesthetizing monitoring unit 110 described herein. The method comprises:

[0186] Step 1210: controlling transmission of a first plurality of stimuli signals 210 using a first set of stimuli signal characteristics.

[0187] Step 1220: receiving input data indicative of response signals 230 received in response to the transmitted stimuli signals, Step 1230: generating an updated set of stimuli signal characteristics using the input data,

[0188] Step 1240: controlling transmission of a second plurality of stimuli signals 220 using the updated set of stimuli signal characteristics.

[0189] In one embodiment, the method further comprises determining a level-of-block, LOBj, value using the received input data, wherein the updated set of stimuli signal characteristics is further generated using the determined LOB value.

[0190] In one embodiment, the stimuli signals comprise one or more pulses, wherein the first set and the updated set of stimuli signal characteristics is at least indicative of a pulse count PC of each stimuli signal or the stimuli signals, wherein generating the updated set of stimuli signal characteristics comprises: increasing pulse count of the updated set of stimuli signal characteristics relative to the first set of stimuli signal characteristics if a calculated signal to noise ratio, SNR, of the response signals is below a first threshold, or, decreasing pulse count of the updated set of stimuli signal characteristics relative to the first set of stimuli signal characteristics if a calculated signal to noise ratio, SNR, of the response signals is equal to or above a second threshold.

[0191] In one example, the SNR is calculated as “detected” or “not detected”. In other words, if one or more response signals / pulses cannot be detected, the pulse count is increased in the next transmission. If al signals / pulses can be detected, the pulse count is decreased in the next transmission.

[0192] In one embodiment, the stimuli signals comprise one or more pulses, wherein the first set and the updated set of stimuli signal characteristics is at least indicative of a pulse frequency f of each stimuli signal or the stimuli signals. Generating the updated set of stimuli signal characteristics then comprises: increasing pulse frequency of the updated set of stimuli signal characteristics relative to the first set of stimuli signal characteristics set if the determined LOB value is above a second threshold, or decreasing pulse frequency of the updated set relative to the first set if the determined LOB value is below the second threshold.

[0193] In one example, the SNR is calculated as “detected” or “not detected”. In other words, if one or more response signals / pulses cannot be detected, the pulse frequency is increased in the next transmission. If al signals / pulses can be detected, the pulse frequency is decreased in the next transmission.

[0194] In one embodiment, the stimuli signal characteristics is at least indicative of a selection of any of pulse amplitude SA of the plurality of pulses, pulse shape of the plurality of pulses and a duration of the stimuli signal.

[0195] In one embodiment, the input data is indicative of pulse amplitude values of the response signals 230.

[0196] In one embodiment, generating the updated set of stimuli signal characteristics then comprises:

[0197] If all of the pulse amplitude values of the response signals 230 are below a first predetermined amplitude threshold, or if a calculated average of the pulse amplitude values of the response signals 230 is below a second predetermined amplitude threshold: generating the updated set of stimuli signal characteristics indicative of a post tetanic count, PTC, stimulation signal.

[0198] In one embodiment, wherein the method further comprises repeating the steps of receiving input data, generating an updated set of stimuli signal characteristics, and controlling transmission of stimuli signals. Additionally, or alternatively, the step of repeating continues until the determined current LOB value is above a predetermined threshold.

[0199] In one non-limiting example, LOB is in the form of TOF ratio or TOFR.

[0200] Additionally, or alternatively, the predetermined threshold is preferably within the range of 90% to 100%, more preferably within the range of 90% to 95% and most preferably 90%.

[0201] According to one further aspect of the disclosure, a method assists the user to understand the current status of the subject / patient and thereby assisting the user in a safer administration of drugs.

[0202] Conventional solutions typically indicate a propriety LOB value, which has the drawback that it is hard for the user to interpret the results.

[0203] In one example, conventional solutions may use stimuli signals with fixed characteristics and TOF ratio. For some levels of block, there may be no recorded responses and hence no result to present. Also, if using multiple monitors, the results may not be comparable.

[0204] Thus, there is a need for an improved method of measuring level of block of a subject. The present disclosure addresses the above-mentioned drawbacks by rendering representations. Rendering of representations is further described at least in relation to Fig. 13, Fig. 21 and Fig. 22.

[0205] Fig. 13 illustrates rendered representations 1310-1390 according to one or more embodiments of the present disclosure. In Fig. 13 the anesthetizing monitoring unit 110 is provided with a display 113 configured to display the rendered representations to a user. In other embodiments, the representations are sent to an external unit, e.g., a wall display or smartphone, for display of the representations 1310-1390.

[0206] The representations may comprise an LOB scale 1310 and a marker 1320 positioned along the LOB scale 1310. The marker indicates to a user the determined LOB value, e.g., along a circular shaped scale ranging from Acceptable Recovery, AR, via minimal, shallow, moderate, deep level of block and complete block. The scale may may in one example be a percentage scale ranging from 0% to 100% block, a normalized scale ranging from 0-1. In other words, the scale may be ranging from any suitable representation representing that the patient is in an acceptable recovery state to that the patient is in a state of complete block. It is understood that the shape of the scale may have any suitable form without departing from the present disclosure.

[0207] In a further example, the marker indicates to a user the determined LOB value as a value between 0% and 100% or between 0 and 100.

[0208] The LOB scale 1310 and the marker 1320 makes it easier for a user to understand the current status of the subject / patient and thereby assisting the user in a safer administration of drugs.

[0209] Additionally, or alternatively, the representations may comprise a graphical representation of pulse count 1330, pulse frequency, pulse amplitude ratio or Post-Tetanic Count / PTC mode indication or a generic LOB scale . The pulse count may e.g., indicate the number of detected pulses in a response signal 230, 240, e.g., TOFC. The pulse amplitude ratio may e.g., indicate TOFR.

[0210] In one example, after a TOF stimulation signal, ideally four pulses should be detected. Generally, a lower pulse count detected in the response signals than the number of pulses in the stimuli signals indicates bad quality of the response signal, e.g., due to deep block or bad connection of electrodes.

[0211] In one example, after a TOF stimulation signal, ideally TOFR > 10% should be observed. Generally, a lower TOFR detected from the response signals than a particular threshold, e.g., 10%, indicates bad quality of the response signal, e.g., due to deep block or bad connection of electrodes. Additionally, or alternatively, the representations may comprise a graphical 1340 and / or text representation 1350 of a calculated elapsed time. The elapsed time indicates time elapsed after the latest plurality of stimuli signal has been sent.

[0212] Additionally, or alternatively, the representations may comprise a graphical and / or text representation of a predicted time 1361 ,1362. The predicted time typically indicates elapsed time + Tseparation, as shown in relation to Fig. 2A.

[0213] Additionally, or alternatively, the representations may comprise stimuli signal characteristics, SSC, e.g., indicative of pulse amplitude 1370 and or pulse duration 1380. The pulse amplitude 1370 may indicate current amplitude of each pulse in the stimuli signal and pulse duration 1380 may indicate pulse width in time or the “on” time of a pulse duty cycle.

[0214] In embodiments, a method performed by a display unit 113 is provided. The display unit 113 may be the anesthetizing monitoring unit 110 or an external unit, such as a wall display, tablet, or smartphone. The method comprises:

[0215] Receiving a signal from the anesthetizing monitoring unit 110 described herein. The signal may be indicative of a selection of level-of-block, LOB; value and corresponding stimuli signal characteristics and optionally any characteristics related to the anesthetizing monitoring unit 110 or subject.

[0216] In one example, the display unit 113 is integrated in the anesthetizing monitoring unit 110 and receives the signal via internal wiring. In a further example, the display unit is a smartphone, and the signal is received via wireless communication, such as Bluetooth or Wi-Fi. In other words, the representations are displayed on a separate device or display, different from the anesthetizing monitoring unit 110.

[0217] Optionally, the method further comprises calculating an elapsed time from a preceding transmission of a first plurality of stimuli signals. The elapsed time may in one example be calculated as elapsed time from the end of the stimuli signal Tstimuii_endi, as further illustrated in relation to Fig. 2A.

[0218] Optionally, the method further comprises calculating a predicted time for an upcoming transmission of a second plurality of stimuli signals. With reference to Fig 2A, the predicted time may be calculated as the end of the stimuli signal Tstimuii_endi and the separation between Stimuli Signals Tseparation .

[0219] The method further comprises rendering a selection of the representations 1310-1370 and a selection of the corresponding stimuli signal characteristics. In one embodiment, the method further comprises receiving input from a user indicative of stopping measurements of LOB via a rendered input symbol 1390, and sending a second signal to the anesthetizing monitoring unit to stop measurements of LOB.

[0220] In one example, the user presses the rendered input symbol 1390 and the LOB monitoring is then paused.

[0221] In embodiments, the representations are selected from any of an LOB scale 1310, a marker 1320 positioned along the LOB scale 1310, a graphical representation of pulse count 1330, a graphical and / or text representation of the calculated elapsed time 1340, 1350, a graphical and / or text representation of the predicted time 1361 ,1362, stimuli signal characteristics indicative of pulse amplitude 1370 and stimuli signal characteristics indicative of pulse duration 1380.

[0222] Fig. 14 illustrates a flowchart of a method 1400 according to one or more embodiments of the present disclosure. The method is performed by the anesthetizing monitoring unit 110 or a display unit 113 described herein. In one embodiment, the display unit 113 may be integrated in the anesthetizing monitoring unit 110 and receives a signal comprising representations 1310-1390 via internal wiring. In a further embodiment, the display unit 113 is a generic patient monitor, a smartphone and / or wall display, and the signal is received via wireless communication, such as Bluetooth or Wi-Fi. In other words, the representations are displayed on a separate device or display, different from the anesthetizing monitoring unit 110.

[0223] The method comprises:

[0224] Step 1410: receiving a signal from the anesthetizing monitoring unit 110 described herein, the signal being indicative of a selection of any of a level-of-block, LOB, value and corresponding stimuli signal characteristics,

[0225] Optional step 1420: calculating an elapsed time from a preceding transmission of a first plurality of stimuli signals.

[0226] With reference to Fig. 2A-B, the elapsed time can be calculated as elapsed time from the first time instant Tstimuii_starti to current time and / or calculated as elapsed time from the second time instant Tstimuii_endi to current time.

[0227] Optional step 1430: calculating a predicted time for an upcoming transmission of a second plurality of stimuli signals.

[0228] With reference to Fig. 2A-B, the predicted time can be calculated as the second time instant Tstimuli_end1 + the separation between stimuli signals Tseparation . Step 1440: rendering a selection of the representations 1310-1390 of the LOB value and / or the corresponding stimuli signal characteristics.

[0229] In one embodiment, the method further comprises:

[0230] Step 1450: receiving input from a user indicative of stopping measurements of LOB via a rendered input symbol 1390.

[0231] Step 1460: sending a second signal to the anesthetizing monitoring unit to stop measurements of LOB.

[0232] Additionally, or alternatively, the representations are selected from any of: an LOB scale 1310, a marker 1320 positioned along the LOB scale 1310, a graphical representation of pulse count 1330, a graphical and / or text representation of the calculated elapsed time 1340, 1350, a graphical and / or text representation of the predicted time 1361 ,1362, stimuli signal characteristics indicative of pulse amplitude 1370, stimuli signal characteristics indicative of pulse duration 1380.

[0233] According to one further aspect of the disclosure, a method assists the user to understand the current status of the subject / patient by a consistent measure indicating the depth of muscular block. In other words, a consistent measure or LOB value is calculated. The LOB value remains the same regardless of stimuli signal characteristics used. This means that the user can follow the depth of muscular block during an entire procedure in an easier and safer manner.

[0234] Conventional solutions typically calculate a propriety LOB value, which has the drawback that it is hard for the user to interpret the results.

[0235] In one example, conventional solutions may use stimuli signals with fixed characteristics and TOF ratio. For some levels of block, there may no recorded responses and hence no result to present. Also, if using multiple monitors, the results may not be comparable.

[0236] Thus, there is a need for an improved method of measuring level of block of a subject.

[0237] Fig. 15 illustrates a further concept of the disclosure according to one or more embodiments of the present disclosure. The plurality of response signals SResponse_i to SResponse_N received in response to the transmitted stimuli signals are typically converted to a data representation as input data, e.g. using analog to digital conversion as further described herein.

[0238] The level-of-block, LOB; value can be determined using the received input data, e.g., amplitudes of the plurality of response signals SResponse_i to SResponse_N. Alternatively, the LOB value is further determined using current stimuli signal characteristics SSCj.*i . Alternatively, the LOB value is further determined using a selection of preceding or historical LOB values LOB;. 1, LOBj-2 , ... , LOBI-M .

[0239] The index i indicates the iteration index of an ordered sequence of the generated LOB value. In other words, the first LOB value determined immediately after measurements have been initiated could be given index=1.

[0240] In one example, the LOB value is determined by relating an amplitude of the first response signal SResponse_i of the plurality of response signals to an amplitude of the last response signal SResPonse_4 of the plurality of response signals, e.g., a T1 calculation of LOB. It is understood that any amplitude of the plurality of response signals may be related each other without departing from the present disclosure.

[0241] The new indication or measure, the LOB value, may be mapped to the existing descriptions (physiological) of depth of block and can be seen as being “calibrated”, e.g., against the degree of block described in the guidelines for NMB monitoring. Alternatively, the indication or measure could be mapped to studies on how muscle groups react to NMBA being administered.

[0242] The present disclosure addresses the shortcomings of conventional methods where the indication or measure of a degree of block linked to a specific measurement method, e.g., a pulse count and time between stimulations TseParation, as further described in relation to Fig. 2.

[0243] In other words, the conventional methods will generate indications or measures of a degree of block which are not easily compared, and the degree of block cannot be easily monitored in a consistent manner.

[0244] The present disclosure introduces a physiological model which takes into account characteristics of the stimuli signals and / or characteristics of the response signals and estimates the response of a subjects body to the stimuli by means of just a few parameters.

[0245] The parameters and / or the physiological model are determined based on observed responses of a subject to a specific stimulation pattern. The parameters may be referred to as fa and fb, as further described in relation to Fig. 18. The parameters are then used as input to a mapping function, referred to as FLINC2, shown in Fig. 18, to determine a result. In other words, as different stimuli signal patterns and different level of block will generate great variations in response signal characteristics, the mapping function FLINC2 will reduce or eliminate these variations in response signal characteristics and instead generate a consistent indication or measure of the level of block of the subject / patient, typically in the form of the LOB value.

[0246] By using the physiological model FLINC1 , the Stimuli Signal Characteristics SSCj+i of the next stimulation may be generated. Additionally, or alternatively, the Stimuli Signal Characteristics SSCj+i of the next stimulation may be generated by the mapping function FLINC2.

[0247] In one example, Stimuli Signal Characteristics SSCj of a first stimulation round are indicative of a TOF stimulation. The response signal characteristics indicate that no pulses can be detected. However, the physiological model FLINC1 still provides the parameters fa and fb allowing the LOB value to be determined by the mapping function FUNC2.

[0248] Fig. 16 illustrates details of determining an LOB value according to one or more embodiments.

[0249] In Fig. 16 three consecutive pluralities of response signals are shown. For illustrative purposes the pulses are shown as square pulses, but it is understood that the response signal may have any suitable shape of signals without departing from the present disclosure.

[0250] A first plurality of response signals S1 , S2, S3 and S4 have substantially the same signal amplitudes and typically illustrates a first response or baseline response before the subject / patient has been administered drugs. The pulse frequency f of the response indicates that pulses are separated by 1 / f seconds. The first pulse, illustrated as a dashed bar, is selected as a baseline value for response amplitudes, e.g., for T1 measure calculations.

[0251] A second plurality of response signals ST, S2’, S3’ and S4’ show falling amplitude values, a phenomenon also referred to as fade. The pulse frequency f’ of the response indicates that pulses are separated by 1 / f’ seconds.

[0252] A third plurality of response signals S1 ”, S2” and S3” also show falling amplitude values or fade. No response signal S4” can be recorded, e.g., due to bad signal quality or signal level no amplitude value can be detected. The pulse frequency f” of the response indicates that pulses are separated by 1 / f’ seconds.

[0253] In one example, the LOB value can be calculated by relating an amplitude of the first response, the amplitude of S1 in this example, to other signal amplitudes such as the amplitude of response signal S4. In one example, the stimuli signal characteristics, SSC, can be adapted by comparing the amplitude value of S1’ to the initial amplitude value S1. The stimuli signal characteristics, SSC, is then adapted by increasing the amplitude of the next stimuli signal in proportion to the fraction S1 / S1’.

[0254] Fig. 17 illustrates a physiological model according to one or more embodiments.

[0255] The present disclosure is in some embodiments based on a realization of how a subject / patient will respond at various level of block, which is described by a physiological model. The physiological model FLING 1 is further described in relation to Fig. 18.

[0256] When the body of the subject generates a response to a stimuli signal, the capability to generate a response or the “energy” goes down with an amount fa. With time the capability to generate a response or the “energy” is restored illustrated by the arrow fb.

[0257] In other words, the present disclosure introduces a model FLINC1 that e.g., takes response signal characteristics S1j, S2j, S3j, S4j and / or stimuli signal characteristics and / or pulse frequency and and / or a baseline amplitude value Sref of the first response as input parameters. The model then outputs fa and fb for the current iteration. Optionally, the model also generates adapted stimuli signal characteristics SSCj+i for an upcoming / the next stimuli signal.

[0258] The model FLINC1 may be implemented as a predetermined relation or function based on measurements, e.g., in a Look Up Table. The model FUNC1 may optionally be a trained model based on scientific studies or other training data comprising known input parameters and known fa and fb.

[0259] Fig. 18 illustrates determining LOB value and adaption of stimuli signal characteristics according to one or more embodiments.

[0260] Response signal characteristics ST, S2j, S3j, S4j, and baseline amplitude value Sref are received and entered into a first model FUNC1 , e.g., a predetermined relation, further described in relation to Fig. 12.

[0261] The first model FUNC1 outputs fa and fb, which are then entered into a second function FUNC2. The second model FUNC2 then outputs the LOB value LOB; and optionally the adapted stimuli signal characteristics SSCj+i.

[0262] In other words, the adapted stimuli signal characteristics SSCj+i for an upcoming / the next stimuli signal may be generated by the first model FUNC1 and / or the second model FUNC2. The first model FLINC1 may be implemented as a predetermined relation or function based on measurements, e.g., in a Look Up Table. The first model FUNC1 may optionally be a trained model based on scientific studies or other training data comprising known input parameters such as Response signal characteristics S1j, S2j, S3;, S4j, and baseline amplitude value Sref, and further known output parameters fa and fb.

[0263] The second model FUNC2 may be implemented as a predetermined relation or function based on measurements, e.g., in a Look Up Table. The second model FUNC2 may optionally be a trained model based on scientific studies or other training data comprising known input parameters fa and fb and a level of block of the subject / patient.

[0264] Fig. 19 illustrates a flowchart of a method 1900 according to one or more embodiments of the present disclosure. The method 1900 is typically performed by the anesthetizing monitoring unit 110 herein. The method comprises:

[0265] Step 1910: controlling transmission of a first plurality of stimuli signals 210 using a first set of stimuli signal characteristics.

[0266] Step 1920: receiving input data indicative of response signals (230) received in response to the transmitted stimuli signals.

[0267] Step 1930: generating parameters fa, fb, indicative of a physiological response of a subject to the first plurality of stimuli signals 210 using the first physiological model FUNC1.

[0268] Step 1940: determining a level-of-block, LOB, value by mapping the generated parameters fa, fb to a Level-Of- Block value using the second model FUNC2.

[0269] In one embodiment, the method 1900 further comprises generating an updated set of stimuli signal characteristics using the input data.

[0270] Fig. 20 illustrates an anesthetizing monitoring unit 110 according to one or more embodiments of the present invention. The measurement interface 105 may further comprise an analog to digital converter, A / D, 1051 configured to receive the response signal SResponse. , sample the response signal SResponse to obtain properties / characteristics of the response signal, such as an amplitude value indicative of signal’s amplitude. The digital converter, A / D, 1051 is further configured to send data indicative of the properties / characteristics of the response signal to the processing circuitry 103.

[0271] In one embodiment, a computer program is provided comprising computer-executable instructions for causing an anesthetizing monitoring unit 110, when the computer-executable instructions are executed on a processing unit comprised in the anesthetizing monitoring unit 110 to perform the method described herein. In one embodiment, a computer program product comprising a computer-readable storage medium, the computer-readable storage medium having the computer program above embodied therein. The memory and / or computer-readable storage medium referred to herein may comprise of essentially any memory, such as a ROM (Read-Only Memory), a PROM (Programmable Read-Only Memory), an EPROM (Erasable PROM), a Flash memory, an EEPROM (Electrically Erasable PROM), or a hard disk drive.

[0272] Moreover, it is realized by the skilled person that the anesthetizing monitoring unit 110 may comprise the necessary communication capabilities in the form of e.g., functions, means, units, elements, etc., for performing the present solution. Examples of other such means, units, elements and functions are: processors, memory, buffers, control logic, mapping units, multipliers, decision units, selecting units, switches, inputs, outputs, antennas, amplifiers, receiver units, transmitter units, DSPs, MSDs, encoder, decoder, power supply units, power feeders, communication interfaces, communication protocols, etc. which are suitably arranged together for performing the present solution.

[0273] Especially, the processor / processing means of the present disclosure may comprise one or more instances of processing circuitry, processor modules and multiple processors configured to cooperate with each-other, Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC), a microprocessor, a Field-Programmable Gate Array (FPGA) or other processing logic that may interpret and execute instructions. The expression “processor” and / or “processing means” may thus represent a processing circuitry comprising a plurality of processing circuits, such as, e.g., any, some or all of the ones mentioned above. The processor / processing means may further perform data processing functions for inputting, outputting, and processing of data comprising data buffering and device control functions, such as call processing control, user interface control, or the like.

[0274] Referring to Fig. 13: To further assist the user to understand the current status of the subject / patient and thereby assisting the user in a safer administration of drugs. Historical values and / or a trend over time for some key indicators, such as the LOB value, is rendered and displayed to the user.

[0275] In other words, by calculating a trend of a selection of preceding and / or historical LOB values and display them in in the same "gauge" as the current LOB value. In one example, historic LOB values are shown together with a current LOB value. It is understood that the LOB values may be aggregated LOB values, such as an average of multiple subsequent LOB values, without departing from the present disclosure In one example, a current LOB value is rendered and displayed together with a historic trend of the LOB value. The trend is important both during the induction phase, the maintenance phase and the recovery phase of anesthesia. In the induction phase the trend shows the speed of which the depth of block increases, it also tells the anesthesiologist when maximum block has been reached (steady state). In the maintenance phase the trend shows if and when the neuromuscular block starts to fade, and it might be time to either inject more NMBA or an antidote. In the recovery phase the trend indicates the need for more anti-dote dosing and also gives a representation of the speed of the spontaneous recovery.

[0276] Fig. 21 illustrates further rendered representations of an LOB current and historical LOB values according to one or more embodiments of the present disclosure. It is understood that the trend of LOB values may be calculated or determined in a similar manner to what is described in relation to Fig. 15 for amplitude values or any other suitable technique to determine trends known to the skilled person.

[0277] In Fig. 21 the anesthetizing monitoring unit 110 is provided with a display 113 configured to display the rendered representations to a user. In other embodiments, the rendered representations are sent to an external unit, e.g., a wall display or smartphone, for display of the representations 1310-1322.

[0278] In the interest of readability, only representations relating to rendering indicators of the current determined LOB value 1320 and historic LOB values 1321 , 1322 are shown. It is understood that any representation, e.g. the ones described in relation to Fig. 13, may be present depending on application without departing from the present disclosure.

[0279] Similar to what is described in relation to Fig. 13, the representations may comprise an LOB scale 1310 and a marker 1320 positioned along the LOB scale 1310. The marker indicates to a user the determined current LOB value, e.g., indicating a current LOB value along a circular shaped scale. The scale may be ranging from Acceptable Recovery, AR, via minimal, shallow, moderate, deep level of block and complete block. The scale may may in one example be a percentage scale ranging from 0% to 100% block, a normalized scale ranging from 0-1. In other words, the scale may may be ranging from any suitable representation representing that the patient is in an acceptable recovery state to that the patient is in a state of complete block. It is understood that the shape of the scale may have any suitable form without departing from the present disclosure. In this embodiment, the currently determined LOB value is displayed as a representation 1320 in the form of a triangle with a solid line.

[0280] A plurality of the most recently determined LOB values, preceding the current determined LOB value, are displayed as representations 1321 , 1322, in the form of a triangles with dotted lines. The plurality of the most recently determined LOB values may comprise two or more LOB values. Any suitable form may be used without departing from the present disclosure that allows the user to differentiate between current and historical values.

[0281] The simultaneous rendering and / or display of the currently determined LOB value and two historically determined LOB values makes it easier for a user to understand the current status of the subject / patient and thereby also to perform safer administration of drugs.

[0282] In one example, if the representations 1320-1322 are relatively highly separated, the status of the patent is rapidly changing over time.

[0283] In one further example, if the representations 1320-1322 are relatively close, the anesthetic status of the patent is slowly changing over time.

[0284] In one further example, if the representations 1320-1322 are largely overlapping, the anesthetic status of the patent is stable or static, as a rate of change of the LOB value

[0285] In one further example, if the representations 1321-1322 are located on a first side, in Fig. 21 the righthand side of the representation of the current LOB value 1320, the anesthetic status of the patent is indicative of a trend towards recovery.

[0286] In one further example, if the representations 1321-1322 are located on an opposite side, in Fig. 21 the lefthand side of the representation of the current LOB value 1320, the anesthetic trend of the patent is indicative of a trend towards deeper block.

[0287] Fig. 22 illustrates further rendered representations of a trend according to one or more embodiments of the present disclosure. It is understood that the trend of LOB values may be calculated or determined in a similar manner to what is described in relation to Fig. 15 for amplitude values.

[0288] In Fig. 22 the anesthetizing monitoring unit 110 is provided with a display 113 configured to display the rendered representations to a user. In other embodiments, the rendered representations are sent to an external unit, e.g., a wall display or smartphone, for display of the representations 1310-1323 .

[0289] In the interest of readability, only representations relating to rendering indicators of the current determined LOB value 1320 and a trend of historic LOB values 1323 are shown. It is understood that any representation, e.g. the ones described in relation to Fig. 13, may be present depending on application without departing from the present disclosure.

[0290] Similar to what is described in relation to Fig. 13, the representations may comprise an LOB scale 1310 and a marker 1320 positioned along the LOB scale 1310. The marker indicates to a user the determined current LOB value, e.g., indicating a current LOB value along a circular shaped scale ranging from Acceptable Recovery, AR, via minimal, shallow, moderate, deep level of block and complete block. The scale may may in one example be a percentage scale ranging from 0% to 100% block, a normalized scale ranging from 0-1 . In other words, the scale may may be ranging from any suitable representation representing that the patient is in an acceptable recovery state to that the patient is in a state of complete block. It is understood that the shape of the scale may have any suitable form without departing from the present disclosure.

[0291] In this embodiment, the current determined LOB value is displayed as a representation 1320 in the form of a triangle with a solid line. A trend of historic LOB values is rendered and displayed as representation 1323, e.g., in the form of a shaded area. Any suitable form may be used to represent the area without departing from the present disclosure.

[0292] In other words, the important characteristic of the rendering of the trend of historic LOB values is to represent from where the LOB value has changed and the rate of that change to the user.

[0293] The trend may e.g., be calculated using a number N of historic LOB values, e.g., the historic LOB values shown as 1321-1322 in Fig. 21.

[0294] The simultaneous rendering and / or display of the currently determined LOB value and the trend of historic LOB values makes it easier for a user to understand the current status of the subject / patient and thereby also to perform safer administration of drugs.

[0295] In one example, if the representations 1323 is relatively large, the status of the patent is rapidly changing over time.

[0296] In one further example, if the representations 1323 is relatively small, the anesthetic status of the patent is slowly changing over time.

[0297] In one further example, if the representations 1320-1322 are largely overlapping, the anesthetic status of the patent is stable or static, as a rate of change of the LOB value

[0298] In one further example, if the representations 1321-1322 are located on a first side, in Fig. 21 the righthand side of the representation of the current LOB value 1320, the anesthetic status of the patent is indicative of a trend towards recovery.

[0299] In one further example, if the representations 1321-1322 are located on an opposite side, in Fig. 22 the lefthand side of the representation of the current LOB value 1320, the anesthetic status of the patent is indicative of a trend towards deeper blocking. Finally, it should be understood that the invention is not limited to the embodiments described above, but also relates to and incorporates all embodiments within the scope of the appended independent claims.

Claims

CLAIMS1. A method (800) performed by the anesthetizing monitoring unit (110), the method comprising: controlling transmission (810) of a first plurality of stimuli signals (210) using a first set of stimuli signal characteristics, receiving (820) input data indicative of response signals (230) received in response to the transmitted stimuli signals, calculating (830) a trend (920) using the received input data, wherein the trend (920) indicates at least amplitude values of one or more response signals (230), estimating (840) an amplitude value (RSC) of a response signal using the calculated trend (920)2. The method according to claim 1 , wherein the amplitude value is estimated for a baseline value (910), wherein the baseline value (910) represents an amplitude of a response signal before the subject has been administered any drugs.

3. The method according to any of the preceding claims, wherein the amplitude value is estimated for a response signal for which no signal could be detected.

4. An anesthetizing monitoring unit (110) configured to measure a level-of-block of a subject, the anesthetizing monitoring unit (110) comprising: an input port (111 ), an output port (112), and processing circuitry (103) being configured to perform the method according to claims 1 -3.

5. An anesthetizing monitoring system (100) configured to measure a level-of-block of a subject, the anesthetizing monitoring system (100) comprising: an anesthetizing monitoring unit (110) according to claim 4, stimulating electrodes (122) electrically coupled to the output port (112) and being configured to receive a stimuli signal from the output port (112) and deliver the stimuli signal to the subject (130), receiving electrodes (121 ) electrically coupled to the input port (111 ) and being configured to obtain a response signal, received in response to the stimuli signal, from the subject (130), the anesthetizing monitoring unit (110) being configured to perform the method according to claims 1 -3.

6. A computer program is provided comprising computer-executable instructions for causing an anesthetizing monitoring unit (110), when the computer-executable instructions are executed on a processing unit comprised in the anesthetizing monitoring unit (110), to perform the method according to claims 1 -3.

7. A computer program product comprising a computer-readable storage medium, the computer-readable storage medium having the computer program according to claim 6 embodied therein.

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