Physiological signal transmission method, physiological signal acquisition edge computing device and medium

Abstract

The invention provides a physiological signal transmission method, a physiological signal acquisition edge computing device and a medium, and the method comprises the steps: obtaining a target bit width based on the peak-to-peak value voltage of a physiological signal acquired by a physiological signal acquisition unit in the physiological signal acquisition edge computing device; compressing the physiological digital signal based on the target bit width to obtain a compressed physiological digital signal; and transmitting the compressed physiological digital signal in the form of a data packet. Compared with a mode of transmitting the uncompressed physiological digital signal in a data packet mode, the mode of transmitting the uncompressed physiological digital signal in the data packet mode has the advantages that the bit width of the compressed physiological digital signal is smaller than that of the uncompressed physiological digital signal, so that the size of the data packet corresponding to the compressed physiological digital signal is smaller than that of the compressed physiological digital signal; the size of the data packet is smaller than that of the data packet corresponding to the physiological digital signal before compression. Therefore, the transmission of the physiological digital signals can be completed in a short time, and the transmission efficiency of the physiological digital signals is improved.

Description

Technical Field

[0001] This disclosure relates to the fields of human factors engineering and data transmission technology, and in particular to a method for transmitting physiological signals, a physiological signal acquisition edge computing device, and a medium. Background Technology

[0002] Human factors engineering is the application of human psychological and physiological principles to the engineering and design of products, processes, and systems. In other words, it is the technology of designing and improving human-machine-environment systems according to human characteristics. In the field of human factors engineering, it usually includes human factors data acquisition equipment, human factors data processing equipment, and corresponding execution equipment. It can also be divided into cloud devices, edge computing devices, and terminal devices.

[0003] Human data acquisition equipment includes physiological signal acquisition edge computing devices. These devices are used to acquire physiological signals, which are characterized by multiple channels, high sampling frequency, and small variations between sampling points. Physiological signal acquisition edge computing devices typically convert physiological analog signals into physiological digital signals, i.e., binary information, to ensure the accuracy of the physiological signals.

[0004] In related technologies, edge computing devices for acquiring physiological signals typically package physiological digital signals into data packets. However, due to the large bit width of physiological digital signals, the resulting data packets are long, leading to longer transmission times and consequently lower transmission efficiency. Summary of the Invention

[0005] One of the technical problems that this disclosure aims to solve is the low transmission efficiency of physiological digital signals.

[0006] To address the aforementioned technical problems, this disclosure provides a method for transmitting physiological signals, a physiological signal acquisition edge computing device, and a medium.

[0007] In a first aspect, embodiments of this disclosure provide a method for transmitting physiological signals, the method comprising: obtaining a target bit width based on the peak-to-peak voltage of a physiological signal acquired by a physiological signal acquisition unit in a physiological signal acquisition edge computing device, wherein the target bit width is smaller than the effective bit width of the analog-to-digital converter in the physiological signal acquisition edge computing device; compressing the physiological digital signal based on the target bit width to obtain a compressed physiological digital signal, wherein the bit width of the compressed physiological digital signal is smaller than the bit width of the physiological digital signal before compression; and transmitting the compressed physiological digital signal in the form of a data packet.

[0008] In some embodiments, obtaining the target bit width based on the peak-to-peak voltage of the physiological signal acquired by the physiological signal acquisition unit in the physiological signal acquisition edge computing device includes: obtaining the peak-to-peak voltage that the physiological signal acquisition unit in the physiological signal acquisition edge computing device can acquire; obtaining the full-scale voltage of the analog-to-digital converter; and obtaining the target bit width based on the full-scale voltage and the peak-to-peak voltage.

[0009] In some embodiments, obtaining the target bit width based on the full-scale voltage and the peak-to-peak voltage includes: obtaining the target bit width based on the ratio of the full-scale voltage to the peak-to-peak voltage.

[0010] In some embodiments, obtaining the target bit width based on the full-scale voltage and the peak-to-peak voltage includes: obtaining the noise voltage of the physiological signal acquisition edge computing device; obtaining the voltage difference between the peak-to-peak voltage and the noise voltage; and obtaining the target bit width based on the ratio of the full-scale voltage to the voltage difference.

[0011] In some embodiments, the method further includes, before transmitting the compressed physiological digital signal in the form of data packets: At least one physiological signal sequence is acquired, wherein each physiological signal sequence includes multiple compressed physiological digital signals, and the physiological digital signals in each physiological signal sequence are acquired through a corresponding signal acquisition channel; Compress at least one physiological signal sequence; The target data packet is obtained based on at least one compressed physiological signal sequence.

[0012] In some embodiments, compressing at least one physiological signal sequence includes: Differential processing is performed on each physiological signal sequence in at least one physiological signal sequence to obtain at least one first differential sequence corresponding to at least one physiological signal sequence, wherein each first differential sequence includes multiple first differential signals; Variable-length encoding is performed on each of the first differential signals in at least one first differential sequence.

[0013] In some embodiments, compressing at least one physiological signal sequence includes: When there are multiple physiological signal sequences, based on the identifier of the signal acquisition channel to which each physiological signal sequence belongs, the physiological digital signals at the same time point in each of the multiple physiological signal sequences are differentially analyzed to obtain multiple second differential sequences corresponding to the multiple physiological signal sequences. The second differential sequence includes multiple second differential signals. Variable-length encoding is performed on each of the second difference signals in multiple second difference sequences.

[0014] In some embodiments, the target data packet includes at least one of the following: the number of signals and the signal bit width; The signal quantity refers to the number of physiological digital signals included in the compressed physiological signal sequence, and the signal bit width refers to the bit width of a single first differential signal included in the first differential sequence.

[0015] Secondly, embodiments of this disclosure provide a physiological signal transmission device, the device comprising: The acquisition module is used to acquire the target bit width based on the peak-to-peak voltage of the physiological signal acquired by the physiological signal acquisition unit in the physiological signal acquisition edge computing device. The target bit width is smaller than the effective bit width of the analog-to-digital converter in the physiological signal acquisition edge computing device. The compression module is used to compress the physiological digital signal based on the target bit width to obtain the compressed physiological digital signal, wherein the bit width of the compressed physiological digital signal is smaller than the bit width of the physiological digital signal before compression. The transmission module is used to transmit compressed physiological digital signals in the form of data packets.

[0016] Thirdly, embodiments of this disclosure provide a physiological signal acquisition edge computing device, including a processor and a memory. The memory stores a program that can run on the processor, and when the program is executed by the processor, it implements the physiological signal transmission method as described in any of the first aspects above.

[0017] Fourthly, embodiments of this disclosure provide a computer-readable storage medium on which a program is stored, and when the program is executed by a processor, it implements a method for transmitting physiological signals as described in any of the first aspects.

[0018] Through the above technical solution, the physiological signal transmission method, physiological signal acquisition edge computing device, and medium provided in this disclosure obtain a target bit width based on the peak-to-peak voltage of the physiological signal acquired by the physiological signal acquisition unit in the physiological signal acquisition edge computing device. The target bit width is smaller than the effective bit width of the analog-to-digital converter in the physiological signal acquisition edge computing device. Then, the physiological digital signal is compressed based on the target bit width to obtain a compressed physiological digital signal, wherein the bit width of the compressed physiological digital signal is smaller than the bit width of the original physiological digital signal. The compressed physiological digital signal is transmitted in the form of data packets. Compared to transmitting the original physiological digital signal in the form of data packets, since the bit width of the compressed physiological digital signal is smaller than that of the original physiological digital signal, the size of the data packets corresponding to the compressed physiological digital signal is smaller than the size of the data packets corresponding to the original physiological digital signal. Therefore, the transmission of physiological digital signals can be completed in less time, thereby improving the transmission efficiency of physiological digital signals. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic flowchart of a physiological signal transmission method disclosed in an embodiment of this disclosure; Figure 2 This is a schematic diagram of the structure of a physiological signal acquisition edge computing device disclosed in an embodiment of this disclosure; Figure 3 This is a schematic flowchart of another physiological signal transmission method disclosed in this embodiment; Figure 4 This is a schematic flowchart of another physiological signal transmission method disclosed in this embodiment; Figure 5 This is a schematic flowchart of another physiological signal transmission method disclosed in this embodiment; Figure 6 This is a schematic diagram of a physiological signal sequence and a corresponding first differential sequence disclosed in an embodiment of this disclosure; Figure 7A This is a schematic diagram of a physiological signal sequence and a corresponding second differential sequence disclosed in an embodiment of the present disclosure; Figure 7BThis is a schematic diagram of another physiological signal sequence and the corresponding second differential sequence disclosed in an embodiment of this disclosure; Figure 8A This is a schematic diagram of the structure of a target data packet disclosed in an embodiment of this disclosure; Figure 8B This is a schematic diagram of the structure of another target data packet disclosed in an embodiment of this disclosure; Figure 8C This is a schematic diagram of the structure of another target data packet disclosed in an embodiment of the present disclosure; Figure 9 This is a block diagram of a physiological signal transmission device disclosed in an embodiment of this disclosure; Figure 10 This is a schematic diagram of another physiological signal acquisition edge computing device disclosed in this embodiment. Detailed Implementation

[0021] The embodiments of this disclosure will be further described in detail below with reference to the accompanying drawings and examples. The detailed description of the embodiments and the accompanying drawings are used to illustrate the principles of this disclosure by way of example, but should not be used to limit the scope of this disclosure. This disclosure can be implemented in many different forms and is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

[0022] These embodiments are provided to make the disclosure thorough and complete, and to fully express the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specifically stated, the relative arrangement of components and steps, material composition, numerical expressions, and values ​​set forth in these embodiments should be interpreted as exemplary only and not as limiting.

[0023] All terms used in this disclosure have the same meaning as understood by one of ordinary skill in the art to which this disclosure pertains, unless otherwise specifically defined. It should also be understood that terms defined in general dictionaries should be interpreted as having meanings consistent with their meanings in the context of the relevant art, and not as idealized or highly formalized, unless expressly defined herein.

[0024] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the specification.

[0025] The physiological signals involved in this disclosure are a variety of measurable signals in the human body, including but not limited to: electrocardiogram (ECG) signals, skin temperature (SKT) signals, photoplethysmogram (PPG) signals, electrodermal activity (EDA) signals, heart rate (HR) signals, electromyogram (EMG) signals, electroencephalogram (EEG) signals, and peripheral capillary oxygen saturation (SPO2) signals.

[0026] In related technologies, edge computing devices for acquiring physiological signals typically package physiological digital signals into data packets. However, due to the large bit width of physiological digital signals, the resulting data packets are long, leading to longer transmission times and consequently lower transmission efficiency.

[0027] This disclosure provides a method for transmitting physiological signals. In this method, a signal processor obtains a target bit width based on the peak-to-peak voltage of the physiological signal acquired by a physiological signal acquisition unit in a physiological signal acquisition edge computing device. The physiological digital signal is then compressed based on the target bit width to obtain a compressed physiological digital signal, thereby reducing the bit width of the physiological digital signal. Compared to transmitting the uncompressed physiological digital signal in the form of data packets, since the bit width of the compressed physiological digital signal is smaller than that of the uncompressed physiological digital signal, the size of the data packets corresponding to the compressed physiological digital signal is smaller than that of the data packets corresponding to the uncompressed physiological digital signal. Therefore, the transmission of the physiological digital signal can be completed in less time, thus improving the transmission efficiency of the physiological digital signal.

[0028] The technical solution of the physiological signal transmission method provided in this disclosure is described below with reference to several specific embodiments: Figure 1 This is a flowchart illustrating a method for transmitting physiological signals disclosed in an embodiment of this disclosure, applied to... Figure 2 The signal processor 201 in the physiological signal acquisition edge computing device 20 shown; such as Figure 1 As shown, the method of this embodiment is as follows: S11: Obtain the target bit width based on the peak-to-peak voltage of the physiological signal acquired by the physiological signal acquisition unit in the physiological signal acquisition edge computing device.

[0029] The target bit width is smaller than the effective bit width of the analog-to-digital converter in the physiological signal acquisition edge computing device.

[0030] The types of physiological signal acquisition edge computing devices 20 include, but are not limited to: electroencephalogram (EEG) signal acquisition devices, electrocardiogram (ECG) signal acquisition devices, and electromyography (EMG) signal acquisition devices; such as Figure 2 As shown, the physiological signal acquisition edge computing device 20 also includes: a physiological signal acquisition unit 202 and an analog-to-digital converter (ADC) 203. One end of the signal processor 201 is connected to one end of the physiological signal acquisition unit 202, and the other end of the signal processor 201 is connected to one end of the ADC 203. The other end of the physiological signal acquisition unit 202 is connected to the other end of the ADC.

[0031] The physiological signal acquisition unit 202 can convert human physical signals into physiological analog signals through analog front-end circuitry. The analog-to-digital converter 203 is used to convert the physiological analog signals into physiological digital signals, which are represented by binary numbers. The physical signals include, but are not limited to, skin temperature, changes in blood volume, and electroencephalogram (EEG) signals. This embodiment uses a physiological voltage signal as an example, where the physiological voltage signal refers to a voltage value.

[0032] In some embodiments, the analog-to-digital converter may include an amplifier and a converter, wherein the amplifier amplifies the physiological voltage signal based on an amplification ratio, and the converter converts the amplified physiological voltage signal into a physiological digital signal.

[0033] The amplifier can be a programmable amplifier, which can amplify the physiological voltage signal to ensure that the physiological digital signal obtained by converting the physiological voltage signal has high accuracy.

[0034] The resolution of an analog-to-digital converter (ADC) represents the bit width of the digital signal output by the ADC under ideal conditions. Ideal conditions refer to a state where the ADC is free of internal noise and nonlinear distortion. The effective number of bits (ENOB) of an ADC refers to the bit width of the digital signal output by the ADC under non-ideal conditions. For example, the resolution of an ADC can be 24 bits, and the ENOB can be 19 bits.

[0035] The ENOB of an analog-to-digital converter (ADC) determines the bit width of the physiological digital signal output by the ADC. For example, if the ENOB of the ADC is N bits, the bit width of the physiological digital signal output by the ADC will be N bits. For instance, if the ENOB of the ADC is 19 bits, then the bit width of the physiological digital signal output by the ADC will be 19 bits.

[0036] For physiological digital signals collected at different times, the bit width of the physiological digital signals obtained by converting the physiological digital signals using an analog-to-digital converter is the same, that is, N bits.

[0037] It should be noted that the target bit width can be a fixed value pre-stored in the signal processor based on experience. For example, the target bit width can be 3 bits.

[0038] However, if the target bit width is a fixed value, the signal processor will compress the physiological digital signal to a fixed target bit width. However, the effective data occupies different bit widths in the physiological digital signal corresponding to the physiological voltage signal acquired at different times. If the target bit width is too large, it may cause information loss in some of the compressed physiological digital signals (e.g., physiological digital signals where the effective data occupies a large bit width). If the target bit width is too small, it may cause redundant bits in some of the compressed physiological digital signals (e.g., physiological digital signals where the effective data occupies a small bit width).

[0039] Therefore, in this embodiment, the target bit width can also be a value determined by the signal processor based on the peak-to-peak voltage of the physiological signal acquired by the physiological signal acquisition unit in the physiological signal acquisition edge computing device and the full-scale voltage of the analog-to-digital converter. This value can be the ratio of the two.

[0040] Among them, the peak-to-peak voltage of physiological signals refers to the peak-to-peak voltage of multiple physiological voltage signals within the sampling period.

[0041] S12: Compress the physiological digital signal based on the target bit width to obtain the compressed physiological digital signal.

[0042] The bit width of the compressed physiological digital signal is smaller than that of the uncompressed physiological digital signal.

[0043] A signal processor can compress the target bit width of a physiological digital signal to reduce its bit width. For example, if the original physiological digital signal has a bit width of 19 bits and the target bit width is 3 bits, the signal processor will compress the 19-bit physiological digital signal by 3 bits, resulting in a 16-bit physiological digital signal.

[0044] Therefore, the signal processor reduces the bit width of the physiological digital signal by compressing the target bit width.

[0045] The signal processor can truncate the high x bits of the physiological digital signal to achieve bit width compression. The high x bits are all 0s, and the bit width of the high x bits is the target bit width, where x is a positive integer.

[0046] Because the physiological voltage signals collected at different times are different, although the bit width of the physiological digital signals obtained by converting different physiological voltage signals is the same (i.e., all are N bits), the bit width occupied by the effective data in different physiological digital signals is different. The effective data refers to the binary number of the physiological digital signal excluding the high x bits. Therefore, for physiological digital signals with high bits of 0, the bit width of the physiological digital signal can be reduced by truncating the high bits of 0.

[0047] S13: Transmit compressed physiological digital signals in the form of data packets.

[0048] The signal processor can package the compressed physiological digital signals into data packets, that is, transmit the physiological digital signals to other devices in the form of data packets. These other devices include, but are not limited to, software platforms, edge computing devices, computers, and servers.

[0049] Specifically, the signal processor obtains the target bit width by measuring the peak-to-peak voltage of the physiological signal acquired by the physiological signal acquisition unit in the physiological signal acquisition edge computing device. The target bit width is smaller than the effective bit width of the analog-to-digital converter in the physiological signal acquisition edge computing device. Then, the physiological digital signal is compressed based on the target bit width to obtain a compressed physiological digital signal, where the bit width of the compressed physiological digital signal is smaller than the bit width of the original physiological digital signal. The compressed physiological digital signal is then transmitted in the form of data packets. Compared to transmitting the original physiological digital signal in the form of data packets, since the bit width of the compressed physiological digital signal is smaller than that of the original physiological digital signal, the size of the data packets corresponding to the compressed physiological digital signal is smaller than the size of the data packets corresponding to the original physiological digital signal. Therefore, the transmission of the physiological digital signal can be completed in less time, thus improving the transmission efficiency of the physiological digital signal.

[0050] In some embodiments of this disclosure, in Figure 1 Based on the illustrated embodiment, the following describes a possible implementation for obtaining the target bit width, such as... Figure 3 As shown, the method of this embodiment is as follows: S121: Obtain the peak-to-peak voltage that the physiological signal acquisition unit in the physiological signal acquisition edge computing device can acquire.

[0051] In different sampling periods, the voltage variation range of multiple physiological voltage signals collected by the physiological signal acquisition edge computing device at multiple sampling times during that sampling period is different. The upper limit of the voltage variation range is the positive peak voltage of the multiple physiological voltage signals, and the lower limit is the negative peak voltage of the multiple physiological voltage signals.

[0052] The signal processor can obtain the peak-to-peak voltage that the physiological signal acquisition unit in the physiological signal acquisition edge computing device can acquire during the sampling period based on the positive and negative peak voltages of multiple physiological voltage signals acquired during each sampling period.

[0053] In some embodiments, the signal processor can obtain the peak-to-peak voltage based on the difference between the positive peak voltage and the negative peak voltage. For example, the peak-to-peak voltage is the difference between the positive peak voltage and the negative peak voltage.

[0054] For example, if the voltage variation range of multiple physiological voltage signals collected within a sampling period is -10mV to 10mV, then the positive peak voltage is 10mV, the negative peak voltage is -10mV, and the peak-to-peak voltage is 20mV; if the voltage variation range of the physiological voltage signal within a sampling period is -1 to 1mV, then the positive peak voltage is 1mV, the negative peak voltage is -1mV, and the peak-to-peak voltage is 2mV.

[0055] Since the voltage variation range of multiple physiological voltage signals collected in different sampling periods is different, the positive peak voltage and / or negative peak voltage of the voltage variation range in different sampling periods are different. Therefore, the signal processor can adaptively obtain the peak-to-peak voltage that the physiological signal acquisition unit in the physiological signal acquisition edge computing device can acquire based on the voltage variation range of multiple physiological voltage signals in the sampling period.

[0056] S122: Obtain the full-scale voltage of the analog-to-digital converter.

[0057] The full-scale voltage of an analog-to-digital converter (ADC) refers to the difference between the maximum and minimum input voltages of the physiological voltage signal that the ADC can convert. For example, the ADC can convert a physiological voltage signal with a maximum input voltage of 2250mV, a minimum input voltage of -2250mV, and a full-scale voltage of 4500mV.

[0058] S123: Obtain the target bit width based on the full-scale voltage and peak-to-peak voltage.

[0059] In some embodiments, the signal processor can obtain the target bit width based on the ratio of full-scale voltage to peak-to-peak voltage.

[0060] The resolution of the analog-to-digital converter (ADC) determines the smallest voltage change unit of the physiological voltage signal that the ADC can resolve, also known as the least significant bit (LSB). The ratio of full-scale voltage to peak-to-peak voltage represents the ratio of a first quantity to a second quantity. The first quantity represents the number of voltage values ​​between the minimum and maximum input voltages that the ADC can represent, while the second quantity is the ratio of peak-to-peak voltage to LSB, and represents the number of voltage values ​​between negative and positive peak voltages among the multiple physiological voltage signals that the ADC can represent.

[0061] Wherein, the first quantity is a fixed value determined based on the resolution of the analog-to-digital converter, and the first quantity is... , The resolution of the analog-to-digital converter (ADC) is the bit width of the physiological digital signal output by the ADC under ideal conditions. The second quantity is... , The actual bit width required to characterize each physiological voltage signal among multiple physiological voltage signals.

[0062] LSB can be the ratio of full-scale voltage to the first quantity.

[0063] The signal processor can use the ratio of the full-scale voltage to the peak-to-peak voltage as a power of 2 to determine the initial bit width, and then apply this ratio to the initial bit width. Round down to obtain the target bit width. To avoid compressing too much bit width, Indicates rounding down. Initial bit width With full-scale voltage Peak-to-peak voltage The relationship between the ratios can be expressed by the following formula:

[0064] in, This represents the ratio of the first quantity to the second quantity. It represents the ratio of full-scale voltage to peak-to-peak voltage.

[0065] For example, if 20mV = 20000μV 187500μV, then , The target bit width is 3 bits; if , but , The target bit width is 6 bits.

[0066] The ratio of full-scale voltage to peak-to-peak voltage, and the first quantity and the second quantity, can satisfy the following relationship:

[0067] because The resolution of the analog-to-digital converter (ADC) is the bit width of the physiological digital signal output by the ADC under ideal conditions. The actual bit width required to characterize each physiological voltage signal among multiple physiological voltage signals. Then... It can characterize the compressible bit width, i.e., the initial bit width. .

[0068] Specifically, the signal processor can adaptively acquire the peak-to-peak voltage that the physiological signal acquisition unit can acquire based on the voltage variation range of the physiological voltage signal, and adaptively acquire the target bit width based on the ratio of the full-scale voltage to the peak-to-peak voltage. This avoids information loss in the physiological digital signal caused by an excessively large target bit width, and avoids redundant bits in the physiological digital signal caused by an excessively small target bit width, thereby improving the accuracy of acquiring the bit width of the physiological digital signal.

[0069] In some embodiments of this disclosure, the physiological signal acquisition edge computing device internally converts human physical signals into physiological voltage signals through multiple devices. For example, the EEG physiological signal acquisition edge computing device internally acquires EEG signals through electrodes, leads, and the interface of the physiological signal acquisition edge computing device, and converts the EEG signals into EEG voltage signals through the physiological signal acquisition unit. Similarly, the medical pulse oximeter internally acquires photocurrent through probe circuits, leads, and the interface of the physiological signal acquisition edge computing device, and generates PPG voltage signals through the physiological signal acquisition unit. Because multiple devices are needed to generate the physiological voltage signals, noise voltages are present in the multiple physiological voltage signals acquired during the sampling period. This noise voltages also exist in the peak-to-peak voltage determined based on the positive and negative peak voltages of the multiple physiological voltage signals during the sampling period, resulting in binary redundancy in the bit width of the compressed physiological digital signal. Therefore, embodiments of this disclosure also provide a method for transmitting physiological signals. Figure 3 Based on the illustrated embodiment, a possible implementation for obtaining the target bit width based on peak-to-peak voltage and full-scale voltage is described, such as... Figure 4 As shown, the method of this embodiment is as follows: S1231: Obtain the noise voltage of the physiological signal acquisition edge computing device.

[0070] The signal processor can test the noise voltage of the physiological signal acquisition edge computing device using a physiological signal generator. For example, the noise voltage can be 10mV.

[0071] In some embodiments, noise voltage may be stored in the signal processor.

[0072] In other embodiments, in a measurement environment where electromagnetic interference noise is less than a preset threshold, the physiological signal generator measures multiple sample physiological voltage signals acquired by the physiological signal acquisition edge computing device through various devices. The signal processor can use the root mean square (RMS) algorithm to perform noise analysis on the multiple sample physiological voltage signals to obtain the noise voltage of the physiological signal acquisition edge computing device. The number of sample physiological voltage signals is at least 1000.

[0073] S1232: Obtain the voltage difference between peak-to-peak voltage and noise voltage.

[0074] The difference between the peak-to-peak voltage and the noise voltage is the corrected peak-to-peak voltage. For example, assuming the peak-to-peak voltage is 20mV and the noise voltage is 10mV, the corrected peak-to-peak voltage is 10mV.

[0075] S1233: Obtain the target bit width based on the ratio of the full-scale voltage to the voltage difference.

[0076] The ratio of full-scale voltage to voltage difference represents the ratio of the first quantity to the third quantity. The third quantity, when noise voltage is removed from the peak-to-peak voltage, represents the number of voltage values ​​between the negative peak voltage and the positive peak voltage that the analog-to-digital converter can represent.

[0077] The signal processor can use the ratio of the full-scale voltage to the voltage difference as a power of 2 to represent the initial bit width, and then apply this ratio to the initial bit width. Round down to obtain the target bit width. This is to avoid compressing too much bit width. Initial bit width The relationship between the voltage difference and the ratio of the full-scale voltage can be expressed by the following formula:

[0078] in, Indicates noise voltage. This represents the voltage difference. For example, if the voltage difference is 100mV and the full-scale voltage is 4500mV, then... ,but The target bit width is 5 bits.

[0079] Specifically, the signal processor corrects the peak-to-peak voltage by subtracting the noise voltage from the peak-to-peak voltage, thereby obtaining a more accurate peak-to-peak voltage. The target bit width is then obtained based on the ratio of the corrected peak-to-peak voltage to the full-scale voltage. The influence of noise generated inside the physiological signal acquisition edge computing device on the physiological voltage signal is taken into account, thereby further eliminating the binary redundancy caused by noise voltage in the bit width of the physiological digital signal.

[0080] In some embodiments of this disclosure, if the signal processor directly assembles multiple compressed physiological digital signals into a data packet, the data packet size may be large, leading to low transmission efficiency. Therefore, embodiments of this disclosure also provide a method for transmitting physiological signals. Figure 1 , Figure 3 and Figure 4 Based on the illustrated embodiment, the method further includes compressing a physiological signal sequence composed of multiple compressed physiological digital signals, such as... Figure 5 As shown, the method of this embodiment is as follows: S51: Obtain at least one physiological signal sequence.

[0081] Each physiological signal sequence may include multiple compressed physiological digital signals. The physiological signal acquisition edge computing device has at least one signal acquisition channel, and each physiological signal sequence corresponds to one signal acquisition channel. The physiological digital signals in each physiological signal sequence are acquired through the corresponding signal acquisition channel. The compressed physiological digital signals are the physiological digital signals with the target bit width compressed as described above.

[0082] For example, suppose the physiological signal acquisition edge computing device has two signal acquisition channels, namely a physiological signal acquisition channel corresponding to the left frontal lobe region of the brain and a physiological signal acquisition channel corresponding to the right frontal lobe region of the brain. Then the signal processor can acquire two physiological signal sequences.

[0083] S52: Compress at least one physiological signal sequence.

[0084] In this process, compared to encapsulating the physiological signal sequence before compression in the form of data packets, the signal processor can compress at least one physiological signal sequence, thereby reducing the total bit width of at least one physiological signal sequence and thus reducing the size of the data packet composed of at least one physiological signal sequence.

[0085] Because the physiological voltage signals acquired through the same signal acquisition channel at adjacent times show little variation, meaning the difference between the physiological voltage signals is small, in each physiological signal sequence, the signal processor acquires the first differential signal between every two adjacent compressed physiological digital signals from multiple compressed physiological digital signals, and further compresses the bit width of the first differential signal. This reduces the bit width of the physiological signal sequence, thereby enabling compression of at least one physiological signal sequence.

[0086] In some embodiments, the process of compressing at least one physiological signal sequence may include steps A1 and A2: A1: Perform differential processing on each physiological signal sequence in at least one physiological signal sequence to obtain at least one first differential sequence corresponding to at least one physiological signal sequence, wherein each first differential sequence includes multiple first differential signals.

[0087] The differential processing can be incremental encoding. For each physiological signal sequence, incremental encoding only records the changes in multiple compressed physiological digital signals in the time dimension. The signal processor can perform differential processing on every two adjacent compressed physiological digital signals in the physiological signal sequence to obtain the first differential sequence corresponding to that physiological signal sequence.

[0088] When there is at least one physiological signal sequence, the signal processor performs differential processing on each physiological signal in the physiological signal sequence to obtain a first differential sequence corresponding to the physiological signal sequence. The first differential sequence also includes the first compressed physiological digital signal from the physiological signal sequence.

[0089] When there are multiple physiological signal sequences, the signal processor performs incremental encoding on each physiological signal sequence to obtain multiple first difference sequences corresponding to the multiple physiological signal sequences. Each first difference sequence also includes the first compressed physiological digital signal from the corresponding physiological signal sequence.

[0090] Figure 6 This is a schematic diagram of a physiological signal sequence and its corresponding first differential sequence disclosed in an embodiment of this disclosure, as shown below. Figure 6As shown, when there is at least one physiological signal sequence, the physiological signal sequence includes n compressed physiological digital signals. For example, physiological signal sequence 1 includes compressed physiological digital signals 1_0 to 1_(n-1), where compressed physiological digital signal 1_0 is the first compressed physiological digital signal in physiological signal sequence 1, and compressed physiological digital signal 1_(n-1) is the nth compressed physiological digital signal in physiological signal sequence 1. The first differential sequence 1 corresponding to physiological signal sequence 1 includes compressed physiological digital signal 1_0 and n-1 first differential signals, where first differential signal 1_1 is the first first differential signal in first differential sequence 1, and first differential signal 1_(n-1) is the (n-1)th first differential signal in first differential sequence 1.

[0091] like Figure 6 As shown, when there are multiple physiological signal sequences, each physiological signal sequence includes n compressed physiological digital signals. Each physiological signal sequence corresponds to a first difference sequence, and each first difference sequence includes a compressed physiological digital signal and n-1 first difference signals.

[0092] refer to Figure 6 Suppose a physiological signal sequence is ,in, This represents the compressed physiological digital signal. , This indicates the sequence number of the compressed physiological digital signal in the physiological signal sequence. Let represent the number of compressed physiological digital signals in the physiological signal sequence. Then, the first difference sequence corresponding to this physiological signal sequence is: ,in, This represents the first differential signal. , , This indicates the sequence number of the first differential signal in the first differential sequence. -1 indicates the number of first differential signals in the first differential sequence.

[0093] A2: Compress each of the first difference signals in at least one first difference sequence.

[0094] For each first difference sequence, there is binary redundancy because the binary sequence of some first difference signals may include leading zeros, that is, the high bits of the first difference signal may be zero.

[0095] In some embodiments, the compression process can be variable-length encoding. For example, the signal processor truncates the leading zeros of the first differential signal and encodes the first differential signal using a sign bit + valid bit + leading zero count method. The sign bit occupies 1 bit; a sign bit of 0 indicates that the first differential signal is positive, and a sign bit of 1 indicates that the first differential signal is negative. The leading zero count occupies 3 bits and is used to represent the number of leading zeros in the first differential signal. The valid bit represents the bits from which leading zeros were removed.

[0096] The signal processor compresses each of the first differential signals in the first differential sequence, thereby representing each of the first differential signals with a smaller bit width, thus achieving compression of the first differential sequence.

[0097] Furthermore, when physiological digital signals are stored, users can determine the address of the physiological digital signal based on its bit width and starting address to access it. Because the bit widths of the compressed first differential signals differ after compression, the signal processor can unify the bit widths of the compressed first differential signals in each first differential sequence to improve the convenience of subsequent random access to each physiological digital signal within the compressed physiological signal sequence. The unified bit width can be the maximum bit width among the multiple compressed first differential signals.

[0098] For example, assuming the compressed physiological digital signal has a bit width of 8 bits, and the physiological signal sequence includes 3 compressed physiological digital signals, represented as follows: The total bit width of this physiological signal sequence is 24 bits, and the first difference sequence corresponding to this physiological signal sequence is... ,in, The corresponding decimal value is +5. The corresponding decimal value is -7. and The compression process is performed, and the bit width is standardized to obtain the compressed result. It can be represented as 0101101, after compression. It can be represented as 0001111, and the compressed physiological signal sequence is: The total bit width of the compressed physiological signal sequence is 22 bits, which is 2 bits more compressed than 24 bits.

[0099] Therefore, by compressing each of the first differential signals in at least one first differential sequence, the signal processor can reduce the size of the data packet composed of at least one physiological signal sequence, thereby improving transmission efficiency.

[0100] Furthermore, since the physiological digital signals in each physiological signal sequence are acquired through a corresponding signal acquisition channel, each physiological signal sequence corresponds to an identifier for a signal acquisition channel of the physiological signal acquisition edge computing device. For example, assuming the physiological signal acquisition edge computing device is an EEG physiological signal acquisition edge computing device, refer to... Figure 6 The identifier for the signal acquisition channel corresponding to physiological signal sequence 1 can be 1: left frontal lobe, and the identifier for the signal acquisition channel corresponding to physiological signal sequence 2 can be 2: right frontal lobe.

[0101] Furthermore, during the actual acquisition of physiological signals by the edge computing device for physiological signal acquisition, the human body acquisition positions corresponding to each signal acquisition channel are close together. Therefore, the difference in physiological signals acquired by any two adjacent signal acquisition channels at the same time point is small. For example, the edge computing device for EEG physiological signal acquisition has multiple electrodes. EEG signals are acquired by wearing an electrode cap on the human body. Each electrode corresponds to one signal acquisition channel. Because the positions of the electrodes on the electrode cap are close together, the potential difference acquired by adjacent electrodes at the same time point is small. Therefore, for each time point, the signal processor acquires the second differential signal between the compressed physiological digital signals at the same time point in any two adjacent physiological signal sequences, and further compresses the bit width of the second differential signal. This can reduce the bit width of multiple physiological signals, thereby enabling the compression of multiple physiological signal sequences.

[0102] In other embodiments, when there are multiple physiological signal sequences, the process of compressing multiple physiological signal sequences may further include steps B1 and B2: B1: Based on the identifier of the signal acquisition channel to which each physiological signal sequence belongs, the physiological digital signals at the same time point in each of the two adjacent physiological signal sequences are differentially analyzed to obtain multiple second differential sequences corresponding to the multiple physiological signal sequences. The second differential sequence includes multiple second differential signals.

[0103] The signal processor, based on the identifiers of multiple signal acquisition channels, arranges these identifiers in ascending order. Then, based on the identifiers of every two adjacent signal acquisition channels, it acquires two physiological signal sequences corresponding to those two channels. Since one physiological signal sequence corresponds to one signal acquisition channel, the signal processor performs differential processing on the physiological digital signals at the same time stamp in every two adjacent physiological signal sequences. Each second differential sequence records the spatial variation of the physiological digital signals at different time stamps.

[0104] In some embodiments, the first second difference sequence among a plurality of second difference sequences may be the first physiological signal sequence among a plurality of physiological signal sequences. The first physiological signal sequence may be the physiological signal sequence corresponding to the signal acquisition channel with the smallest identifier, or it may be the physiological signal sequence corresponding to the signal acquisition channel with the largest identifier.

[0105] Figure 7A This is a schematic diagram of a physiological signal sequence and a corresponding second differential sequence disclosed in an embodiment of this disclosure, as shown below. Figure 7A As shown, each of the multiple physiological signal sequences includes compressed physiological digital signals corresponding to n timestamps. Each physiological signal sequence corresponds to a second difference sequence, and each second difference sequence includes n second difference signals. For example, the second difference sequence corresponding to physiological signal sequence 1 is second difference sequence 1, the compressed physiological digital signal 1_0 is the first second difference signal in second difference sequence 1, and the compressed physiological digital signal 1_(n-1) is the nth second difference signal in second difference sequence 1; the second difference sequence corresponding to physiological signal sequence 2 is second difference sequence 2, the second difference signal 2_0 is the first second difference signal in second difference sequence 2, and the second difference signal 2_(n-1) is the nth second difference signal in second difference sequence 1.

[0106] In other embodiments, the first second differential sequence among a plurality of second differential sequences may be the first differential sequence after differential processing of the first physiological signal sequence among a plurality of physiological signal sequences. The first physiological signal sequence may be the physiological signal sequence corresponding to the signal acquisition channel with the smallest identifier, or it may be the physiological signal sequence corresponding to the signal acquisition channel with the largest identifier.

[0107] Figure 7B This is a schematic diagram of another physiological signal sequence and the corresponding second differential sequence disclosed in this embodiment of the present disclosure, as shown below. Figure 7B As shown, in the second differential sequence 1 corresponding to the physiological signal sequence 1, the compressed physiological digital signal 1_0 is the first second differential signal, the first differential signal 1_1 is the second second differential signal, and the first differential signal 1_(n-1) is the nth second differential signal.

[0108] refer to Figure 7A Assuming physiological signal sequence 1 is Physiological signal sequence 2 is The physiological signal sequence m is Then the second difference sequence corresponding to physiological signal sequence 1 is: The second difference sequence corresponding to the physiological signal sequence m is in, This represents the second differential signal. , , , Indicates the index of the second difference sequence. This indicates the sequence number of the second differential signal in the second differential sequence. This indicates the number of the second difference sequence. This indicates the number of second differential signals in the second differential sequence.

[0109] B2: Compress each second difference signal in multiple second difference sequences.

[0110] For each second differential sequence, since the binary sequence of the second differential signal may also include leading zeros, that is, the high bits of the second differential signal may be zero, resulting in binary redundancy.

[0111] In some embodiments, when the first second differential sequence is the first physiological signal sequence among multiple physiological signal sequences, the signal processor can compress each second differential signal in the remaining second differential sequences other than the first physiological signal sequence, thereby representing each second differential signal with a smaller bit width, thus achieving compression of multiple second differential sequences.

[0112] Furthermore, the signal processor can unify the bit width of the compressed second differential signal in each second differential sequence. The unified bit width can be the maximum bit width among multiple compressed second differential signals.

[0113] Therefore, by compressing each second differential signal in multiple second differential sequences, the signal processor can reduce the size of the data packet composed of multiple physiological signal sequences, thereby improving transmission efficiency.

[0114] In other embodiments, when the first second differential sequence is the first differential sequence corresponding to the first physiological signal sequence among multiple physiological signal sequences, the signal processor can compress the first differential signal in the first differential sequence and the second differential signal in the other second differential sequences besides the first differential sequence, thereby achieving compression of the first differential sequence and multiple second differential sequences.

[0115] S53: Obtain the target data packet based on at least one compressed physiological signal sequence.

[0116] The signal processor can package at least one compressed physiological signal sequence to obtain a target data packet.

[0117] In some embodiments, the target data packet may further include at least one of the number of signals and the signal bit width; wherein the number of signals is the number of physiological digital signals included in the compressed physiological signal sequence, and the signal bit width is the bit width of a single first differential signal included in the first differential sequence.

[0118] The number of signals can occupy one byte, and the signal width can also occupy one byte. Because the signal processor compresses each first differential signal in the first differential sequence and unifies the bit width of each first differential signal, the bit width of each first differential signal in the first differential sequence is the same, and the bit width of a single first differential signal is the bit width of any one of the multiple first differential signals.

[0119] When there is at least one compressed physiological signal sequence, this compressed physiological signal sequence can be a first differential sequence. The signal processor assembles this first differential sequence into a target data packet. In this case, the target data packet includes physiological digital signals acquired by a signal acquisition channel, as referenced... Figure 8A The target data packet may include: a packet header, a signal quantity, a signal bit width, a compressed physiological digital signal, and multiple first differential signals; the signal quantity is the number of compressed physiological digital signals and first differential signals, and the signal bit width is the bit width of a single first differential signal. For example, assuming that the target data packet includes a signal acquisition channel called signal acquisition channel 1, then the signal quantity 1 is the number n of compressed physiological digital signals 1_0 to first differential signals 1_(n-1), which can be 128; the signal bit width 1 is the bit width of a single first differential signal among the first differential signals 1_1 to first differential signals 1_(n-1), which can be 8 bits.

[0120] When there are multiple compressed physiological signal sequences, these multiple compressed physiological signal sequences can be multiple first difference sequences or multiple second difference sequences.

[0121] If the multiple compressed physiological signal sequences are multiple first-difference sequences, the signal processor assembles these multiple first-difference sequences into a target data packet. In this case, the target data packet includes physiological digital signals acquired by multiple signal acquisition channels. (Reference) Figure 8AThe target data packet includes: a packet header, m signal counts, m signal bit widths, and physiological digital signals acquired by m signal acquisition channels. Each signal acquisition channel corresponds to one signal count, one signal bit width, and one compressed physiological digital signal and multiple first differential signals in the corresponding first differential sequence. The signal count corresponding to each signal acquisition channel is the number of compressed physiological digital signals and first differential signals in the corresponding first differential sequence, and the signal bit width corresponding to each signal acquisition channel is the bit width of the first differential signal in the corresponding first differential sequence. For example, the signal count m corresponding to signal acquisition channel m is the number n of compressed physiological digital signals m_0 to first differential signals m_(n-1), which can be 128, and the signal bit width m is the bit width of a single first differential signal in the first differential signals m_1 to first differential signals m_(n-1), which can be 8 bits.

[0122] In some embodiments, if the plurality of compressed physiological signal sequences constitute a single physiological signal sequence and a plurality of second differential sequences, the signal processor assembles the single compressed physiological signal sequence and the plurality of second differential sequences into a packet to obtain a target data packet. In this case, refer to Figure 8B The target data packet includes: a header, a signal quantity, a signal bit width, and physiological digital signals acquired by m signal acquisition channels. Signal acquisition channel 1 corresponds to a signal quantity of 1, a signal bit width of 1, and multiple compressed physiological digital signals in the corresponding physiological signal sequence. Each of the other signal acquisition channels corresponds to multiple second differential signals. The signal quantity of 1 is the total number of compressed physiological digital signals, and the signal bit width of 1 is the bit width of the first differential signal. For example, the signal quantity of 1 is the number n of compressed physiological digital signals 1_0 to 1_(n-1), which can be 128. Since the physiological signal sequence corresponding to signal acquisition channel 1 does not include the first differential signal, the signal bit width of 1 is 0.

[0123] In other embodiments, if the multiple compressed physiological signal sequences are a first differential sequence and multiple second differential sequences, the signal processor assembles the first differential sequence and multiple second differential sequences into a packet to obtain a target data packet. In this case, refer to Figure 8CThe target data packet includes: a header, a signal quantity, a signal bit width, and physiological digital signals acquired by m signal acquisition channels. Signal acquisition channel 1 corresponds to a signal quantity of 1, a signal bit width of 1, and a compressed physiological digital signal and multiple first differential signals in the corresponding first differential signal sequence. Each of the other signal acquisition channels corresponds to multiple second differential signals. The signal quantity of 1 is the number of compressed physiological digital signals and multiple first differential signals in the first differential sequence corresponding to signal acquisition channel 1, and the signal bit width of 1 is the bit width of a single first differential signal. For example, the signal quantity of 1 is the number n of compressed physiological digital signals 1_0 to first differential signals 1_(n-1), which can be 128, and the signal bit width of 1 is the bit width of a single first differential signal in first differential signals 1_1 to first differential signals 1_(n-1), which can be 8 bits.

[0124] Because the bit width of the compressed physiological signal sequence is smaller than that of the uncompressed physiological signal sequence, the length of the target data packet composed of at least one compressed physiological signal sequence is shorter than that of a data packet composed of at least one uncompressed physiological signal sequence, meaning the size of the target data packet is smaller.

[0125] Specifically, the signal processor reduces the bit width of at least one physiological signal sequence by compressing it, and then obtains the target data packet based on the compressed physiological signal sequence. This reduces the size of the data packet, the transmission time of the data packet, and thus improves the transmission efficiency of the physiological digital signal.

[0126] In some embodiments of this disclosure, after the signal processor transmits multiple target data packets to other devices, the other devices can unpack each target data packet to obtain at least one compressed physiological signal sequence corresponding to the target data packet. The signal processor can also decompress the at least one compressed physiological signal sequence to obtain at least one corresponding physiological signal sequence.

[0127] In this process, where the compressed physiological signal sequence is a first differential sequence, the processor in other devices can decompress each of the first differential signals in the first differential sequence and integrate one compressed physiological digital signal and multiple first differential signals in the first differential sequence to obtain the physiological signal sequence. The bit width of the decompressed first differential signal is the same as the bit width of the compressed physiological digital signal in the physiological signal sequence. If the differential processing is incremental encoding, then the integration processing is incremental decoding, which is the inverse process of incremental encoding; if the compression method is variable-length encoding, then the decompression method is variable-length decoding, which is the inverse process of variable-length encoding.

[0128] When there are multiple compressed physiological signal sequences, and these multiple compressed physiological signal sequences constitute a single physiological signal sequence and multiple second differential sequences, the processor in other devices can decompress each second differential signal in each second differential sequence, and integrate the compressed physiological digital signal and second differential signal at the same timestamp in the physiological signal sequence and the multiple second differential sequences to obtain multiple physiological signal sequences. The bit width of the decompressed second differential signal is the same as the bit width of the compressed physiological digital signal in the physiological signal sequence.

[0129] When there are multiple compressed physiological signal sequences, and these multiple compressed physiological signal sequences are a first differential sequence and multiple second differential sequences, the processor in other devices can decompress each first differential signal in the first differential sequence and each second differential signal in each second differential sequence, and perform integration processing on the first differential sequence to obtain the physiological signal sequence corresponding to the first differential sequence; the processor in other devices can also perform integration processing on the physiological signal sequence and the compressed physiological digital signals and second differential signals at the same timestamp in the multiple second differential sequences to obtain multiple physiological signal sequences.

[0130] Processors in other devices can also supplement the compressed physiological digital signal with high-order zeros based on the effective bit width of the analog-to-digital converter and the bit width of the compressed physiological digital signal, to obtain a physiological signal with a bit width equal to the effective bit width of the analog-to-digital converter. The number of high-order zeros is the difference between the effective bit width and the bit width of the compressed physiological digital signal.

[0131] Furthermore, the signal processor can store multiple target data packets in the internal memory of the physiological signal acquisition edge computing device. For example, this memory could be a memory card.

[0132] Figure 9 This is a block diagram of a physiological signal transmission device disclosed in this disclosure, such as... Figure 9 As shown, the device includes: The acquisition module 901 is used to acquire the target bit width based on the peak-to-peak voltage of the physiological signal acquired by the physiological signal acquisition unit in the physiological signal acquisition edge computing device, wherein the target bit width is smaller than the effective bit width of the analog-to-digital converter in the physiological signal acquisition edge computing device. Compression module 902 is used to compress physiological digital signals based on a target bit width to obtain compressed physiological digital signals, wherein the bit width of the compressed physiological digital signals is smaller than the bit width of the physiological digital signals before compression. The transmission module 903 is used to transmit compressed physiological digital signals in the form of data packets.

[0133] In some embodiments, the acquisition module 901 is used to acquire the peak-to-peak voltage that the physiological signal acquisition unit in the physiological signal acquisition edge computing device can acquire; acquire the full-scale voltage of the analog-to-digital converter; and acquire the target bit width based on the ratio of the full-scale voltage to the peak-to-peak voltage.

[0134] In some embodiments, the acquisition module 901 is used to acquire the noise voltage of the physiological signal acquisition edge computing device; acquire the voltage difference between the peak-to-peak voltage and the noise voltage; and acquire the target bit width based on the ratio of the full-scale voltage to the voltage difference.

[0135] In some embodiments, the compression module 902 is used to acquire at least one physiological signal sequence, wherein each physiological signal sequence includes multiple compressed physiological digital signals, and the physiological digital signals in each physiological signal sequence are acquired through a corresponding signal acquisition channel; to compress the at least one physiological signal sequence; and to acquire a target data packet based on the at least one compressed physiological signal sequence.

[0136] In some embodiments, the compression module 902 is used to perform differential processing on each physiological signal sequence in at least one physiological signal sequence to obtain at least one first differential sequence corresponding to at least one physiological signal sequence, wherein each first differential sequence includes multiple first differential signals; and to perform compression processing on each first differential signal in at least one first differential sequence.

[0137] In some embodiments, the compression module 902 is configured to, when there are multiple physiological signal sequences, perform differential analysis on the physiological digital signals at the same timestamp in each pair of adjacent physiological signal sequences based on the identifier of the signal acquisition channel to which each physiological signal sequence belongs, to obtain multiple second differential sequences corresponding to the multiple timestamps of the multiple physiological signal sequences, wherein the second differential sequences include multiple second differential signals; and perform variable-length encoding on each of the multiple second differential signals in the multiple second differential sequences.

[0138] In some embodiments, the target data packet includes at least one of: signal quantity and signal bit width; wherein, the signal quantity is the number of first differential signals included in the compressed physiological signal sequence, and the signal bit width is the bit width of the first differential signal included in the first differential signal sequence.

[0139] The device in this embodiment can be used to execute the physiological signal transmission method of the above embodiment. Its implementation principle and technical effect are similar, and will not be described again here.

[0140] Figure 10 This is a schematic diagram of the structure of another physiological signal acquisition edge computing device disclosed in this disclosure, as shown below. Figure 10As shown, the physiological signal acquisition edge computing device 20 further includes: a memory 204 and a computer program stored on the memory 204 and executable on the signal processor 201. The memory 204 is connected to the signal processor 201. When the signal processor 201 executes the computer program, it implements the physiological signal transmission method as described in the above embodiment.

[0141] This disclosure also provides a computer-readable storage medium on which a program is stored, which, when executed by a processor, implements the method for transmitting physiological signals as described in the above embodiments.

[0142] The embodiments of this disclosure have now been described in detail. To avoid obscuring the concept of this disclosure, some details known in the art have not been described. Those skilled in the art can fully understand how to implement the technical solutions disclosed herein based on the above description.

[0143] While specific embodiments of this disclosure have been described in detail by way of examples, those skilled in the art should understand that the examples are for illustrative purposes only and not intended to limit the scope of this disclosure. Those skilled in the art should understand that modifications can be made to the above embodiments or equivalent substitutions can be made to some technical features without departing from the scope and spirit of this disclosure. In particular, as long as there is no structural conflict, the technical features mentioned in the various embodiments can be combined in any manner.

Claims

1. A method of transmitting a physiological signal, characterized by, The physiological signal collection edge computing device comprises: Based on the peak-to-peak voltage of the physiological signal collected by the physiological signal collection unit in the physiological signal collection edge computing device, a target bit width is obtained, wherein the target bit width is less than the effective bit width of the analog-to-digital converter in the physiological signal collection edge computing device; Based on the target bit width, the physiological digital signal is compressed to obtain the compressed physiological digital signal, wherein the bit width of the compressed physiological digital signal is less than the bit width of the physiological digital signal before compression; The compressed physiological digital signal is transmitted in the form of a data packet.

2. The method of claim 1, wherein, Based on the peak-to-peak voltage of the physiological signal collected by the physiological signal collection unit in the physiological signal collection edge computing device, a target bit width is obtained, comprising: The full-scale voltage of the analog-to-digital converter is obtained; Based on the full-scale voltage and the peak-to-peak voltage, the target bit width is obtained.

3. The method of claim 2, wherein, Based on the full-scale voltage and the peak-to-peak voltage, the target bit width is obtained, comprising: Based on the ratio of the full-scale voltage to the peak-to-peak voltage, the target bit width is obtained.

4. The method of claim 2, wherein, Based on the full-scale voltage and the peak-to-peak voltage, the target bit width is obtained, comprising: The noise voltage of the physiological signal collection edge computing device is obtained; The voltage difference between the peak-to-peak voltage and the noise voltage is obtained; Based on the ratio of the full-scale voltage to the voltage difference, the target bit width is obtained.

5. The method according to any one of claims 1 to 4, characterized in that, Before transmitting the compressed physiological digital signal in the form of a data packet, the method further comprises: At least one physiological signal sequence is obtained, wherein each physiological signal sequence comprises a plurality of compressed physiological digital signals, and the physiological digital signal in each physiological signal sequence is collected through a corresponding signal collection channel; At least one physiological signal sequence is compressed; Based on at least one compressed physiological signal sequence, a target data packet is obtained.

6. The method of claim 5, wherein, Compressing at least one physiological signal sequence comprises: Each physiological signal sequence in at least one physiological signal sequence is subjected to differential processing to obtain at least one first differential sequence corresponding to at least one physiological signal sequence, wherein each first differential sequence comprises a plurality of first differential signals; Each first differential signal in at least one first differential sequence is subjected to compression processing.

7. The method of claim 5, wherein, Compressing at least one physiological signal sequence comprises: In the case of multiple at least one physiological signal sequences, based on the identification of the signal collection channel to which each physiological signal sequence belongs, the physiological digital signals of the same timestamp in each adjacent two physiological signal sequences in the plurality of physiological signal sequences are differentiated to obtain a plurality of second differential sequences corresponding to the plurality of physiological signal sequences, wherein the second differential sequence comprises a plurality of second differential signals; Each second differential signal in the plurality of second differential sequences is subjected to compression processing.

8. The method of claim 6, wherein: The target data packet further comprises at least one of the number of signals and the bit width of the signals. The signal quantity is the quantity of physiological digital signals included in the compressed physiological signal sequence, and the signal bit width is the bit width of a single first difference signal included in the first difference sequence.

9. A physiological signal acquisition edge computing device, characterized by, The physiological signal transmission device comprises a physiological signal acquisition unit, an analog-to-digital converter, a signal processor and a memory, wherein the memory stores a program executable on the signal processor, and the program is executed by the signal processor to implement the physiological signal transmission method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a program, and the program is executed by the processor to implement the physiological signal transmission method according to any one of claims 1 to 8.

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