324 results about "Electrical impedance" patented technology

The invention relates to the technical field of connector layout optimization, and discloses a high-density four-row connector layout intelligent optimization method. The method comprises the steps that design parameters of four rows of connectors on the high-density circuit board are collected, the design parameters comprise connector position coordinates, the number of pins and electrical impedance values, and related environment data comprise temperature distribution, electromagnetic interference intensity and vibration frequency; performing standardized alignment processing on the design parameters and the environment data to form a layout data set with unified dimensions; the layout optimization model is used for processing the layout data set, an initial layout scheme is generated, and the initial layout scheme comprises connector arrangement sequence and position adjustment suggestions; monitoring change data of the working state of the circuit board in real time, wherein the change data comprise current fluctuation and heat distribution updating; and identifying a layout abnormal condition based on the change data, performing iterative correction on the initial layout scheme according to the layout abnormal condition, and outputting a final optimized layout scheme. The method can dynamically adapt to the working state of the equipment and improve the layout rationality.

The invention discloses a bioelectrical impedance tumor detection method based on pattern recognition, and the method comprises the following steps: S1, carrying out the electrical impedance measurement of a to-be-detected tumor region through a bioelectrical impedance analysis instrument, and obtaining the current, voltage and impedance values at different depths and frequencies; s2, designing a feature extraction module, and extracting key features in the electrical impedance data of each channel under different frequencies; s3, inputting the extracted key features into a multi-level feature fusion module, and fusing the electrical impedance features under different channels and frequencies to form new fused features; and S4, inputting the fusion features into a self-adaptive classification module, and adjusting model parameters in combination with a self-adaptive optimization method. According to the invention, automatic processing and classification are carried out on data through a pattern recognition algorithm, and the accuracy, sensitivity and reliability of tumor detection can be effectively improved in combination with the feature extraction module, the multi-level feature fusion module and the adaptive classification module.

The invention relates to the field of electrical impedance detection, in particular to a three-dimensional electrical impedance distribution monitoring method and system, and the method comprises the steps: detecting and analyzing the physical attribute data of all target points on an object, and dividing all target points into a first-choice applied excitation point set and an alternative applied excitation point set; based on the spatial distribution state of all target points subordinate to the preferred applied excitation point set and the contact state between all the target points and the electrode, adjusting the preferred applied excitation point set by using the alternative applied excitation point set; and determining electrical impedance information of all target points based on the excitation current signals applied to all the target points subordinate to the preferred applied excitation point set and the generated response voltage signals, integrating the electrical impedance information to generate a three-dimensional electrical impedance distribution image of the object, and determining an electrical impedance abnormal region of the object. According to the invention, electrical impedance detection in a global range can be carried out on an object with an irregular three-dimensional shape and anisotropic organization structure state, and the three-dimensional electrical impedance distribution condition of the object is obtained.

The invention discloses an electrical impedance cancer detection method based on a self-attention mechanism. The method comprises the following steps: S1, acquiring an electrical impedance signal and sending the electrical impedance signal into an input layer for preprocessing; s2, the preprocessed signal is divided into two branches, the first branch is input into a frequency domain network to extract frequency domain features of the signal, and the second branch is input into a time domain model to extract high-dimensional features of the signal; s3, inputting the frequency domain features extracted by the frequency domain network and the high-dimensional features extracted from the time domain model into a feature fusion layer for fusion; and S4, processing the fused features by using a self-attention mechanism, finally transmitting the processed features to a full connection layer and a classification output layer for cancer risk prediction, and outputting a detection result. According to the method, the frequency domain features and the high-dimensional features are extracted through the frequency domain network and the time domain model respectively and then fused, the fused features are enhanced by using a self-attention mechanism, and the accuracy and reliability of cancer detection are improved.

The invention provides a high-bandwidth working condition simulation test method and system based on virtual impedance control, and the method comprises the steps: building virtual impedance through an electrical impedance model and a digital low-pass filter or a target working condition model; the control bandwidth of the working condition simulation system can be obviously improved under the conditions that a differential operator is not directly used, control parameters are not improved and the stability margin is not sacrificed; meanwhile, the high-bandwidth working condition simulation test system still comprises a closed-loop control structure, so that the voltage stress and the current stress of the converter to be tested can be simulated more accurately. In addition, the simulation converter is adopted to reproduce the voltage and current stress of the converter to be tested; a current-mode / voltage-mode impedance network is adopted to suppress differential-mode current / voltage ripples and differential-mode current / current harmonics; a ripple passive suppression module and a ripple active suppression module are adopted to suppress common-mode current ripples, and the size and the cost of the ripple passive suppression module are reduced.

The invention relates to the field of electrical impedance detection, in particular to a resistance impedance detection probe control method, device and system, and the method comprises the steps: detecting the liquid state characteristics of the environment where a resistance impedance detection probe is located, so as to estimate the liquid ion flowing space distribution information of the surface of the probe; estimating a bioelectricity signal drift change characteristic formed by liquid ions in a detection coverage range corresponding to the electrode, and adjusting an electric signal detection parameter of the electrode; adjusting signal processing parameters of signal processing ends corresponding to the electrodes on the basis of change characteristics of bioelectricity signal queues acquired by all the electrodes on the surface of the probe; and based on the resistance impedance information generated by the signal processing end and the position change information of all the electrodes on the surface of the probe in the environment, a resistance impedance distribution image is generated, so that a resistance impedance abnormal area in the environment is determined. The working state of the probe can be adjusted in the changing process of the liquid environment in the human tissue, and therefore the bio-electricity signal of the liquid environment is accurately detected.

The invention relates to the technical field of signal processing, and provides a muscle state analysis method and device based on electrical impedance measurement, equipment and a storage medium. The muscle state analysis method based on electrical impedance measurement comprises the following steps: acquiring electrical impedance data and myoelectricity data of a target muscle group; extracting electrical impedance characteristics based on the electrical impedance data, and extracting myoelectricity characteristics based on the myoelectricity data; fusing the electrical impedance feature and the myoelectricity feature to obtain a fused feature vector; and inputting the fusion feature vector into a pre-constructed muscle state evaluation model for analysis to obtain a muscle state. By combining the myoelectricity data and the electrical impedance data, the muscle state is accurately evaluated from multiple dimensions, and therefore the accuracy and reliability of muscle state evaluation are improved.

The invention discloses a photovoltaic string fault positioning method based on a dynamic threshold value and topology analysis. The method comprises the following steps: firstly, collecting current, voltage, temperature and illumination intensity data of a string in real time; then, generating a fault judgment threshold dynamically adjusted along with the environment based on historical data and an LSTM model; then, comparing the real-time data with a dynamic threshold value to detect an abnormal node; then, constructing a string topology network taking electrical impedance as a weight, and accurately positioning a fault point by using a Dijkstra shortest path algorithm; and finally, multi-dimensional features are extracted, specific fault types such as hot spots and open circuits are identified through a fuzzy logic classifier, and a diagnosis report is output. According to the method, the problems that the static threshold false alarm rate is high and the traditional topology analysis precision is insufficient are solved, rapid and accurate positioning and diagnosis of photovoltaic faults are realized, and the operation and maintenance efficiency is improved.

The invention provides a tumor recognition method based on multi-modal feature fusion, relates to the technical field of tumor recognition, and is used for solving the problems of missing multi-modal feature calibration, insufficient semantic association, poor generalization and insufficient clinical interpretability in the prior art. The method comprises the following steps: firstly, synchronously acquiring visual structure and electrical impedance bimodal data through an event-driven sensor array, and completing preprocessing through pulse coding, STDP rule optimization and quality verification; then, respectively extracting structured feature vectors of a tumor visual structure class and characteristic feature vectors of a numerical attribute class by a heterogeneous twin coding engine, and unifying dimensions and distribution through processes such as multi-scale dynamic perception and cross-modal calibration; then based on an attention mechanism, InfoNCE contrast loss and minority class weight gain, dynamic weighted fusion and semantic association enhancement are performed on the bimodal features, and a comprehensive feature vector is generated; and finally, through clinical logic adaptation and multi-center deviation correction, outputting a tumor benign and malignant identification result through a full-connection classifier, and synchronously generating a clinical interpretable report containing key features and weights. According to the method, the complementary advantages of bimodal information are effectively integrated, the problems of heterogeneous multi-center equipment, unbalanced samples and the like are solved, the tumor recognition accuracy and the early-stage tiny tumor detection rate are improved, the computing power consumption is reduced, edge medical equipment deployment is adapted, and the requirements for low misjudgment and traceability of clinical diagnosis are met.

A system to determine the transfection status of at least one cell in a population of cells includes a fluidic device comprising a microfluidic channel and a detection zone comprising a detection electrode module comprising two electrodes configured to detect electrical impedance between the electrodes transversely across the channel in the detection zone; corresponding to a cell passing the detection zone, a pump fluidically coupled to the fluidic device and configured to pump the population of cells in a carrier liquid along the microfluidic channel, and a processor operatively coupled to the detection electrode module and configured to detect a change in electrical impedance corresponding to a cell passing the detection zone, compare the change in electrical impedance with a reference change in electrical impedance corresponding to a cell of known transfection status, and calculate the transfection status of the cell based on the comparison.

The invention discloses a multi-modal tumor identification method based on a frequency domain attention mechanism. The method comprises the following steps: S1, acquiring multi-frequency bioelectrical impedance signals of tumor tissues and normal tissues and corresponding medical tumor pathological images; s2, extracting a frequency-time feature of the electrical impedance signal and a spatial feature of the pathological image through a multi-modal feature coding module, and generating a multi-modal fusion feature; s3, converting the multi-modal fusion features into frequency domain representation, performing weighted enhancement on the multi-modal fusion features through a frequency domain attention module, and outputting the features; and S4, fusing the features output by the frequency domain attention module and the superficial layer features in the coding stage through jump connection to obtain enhanced features, inputting the enhanced features into a decoding network, and outputting a tumor classification result. According to the method, the bioelectrical impedance signal and the multi-modal information of the pathological image are fused, and a frequency domain attention mechanism is introduced to effectively improve the expression ability of key frequency characteristics.

A portable, multimodal dental diagnostic device for assessing the vitality of the dental pulp, consisting of: a detachable diagnostic component comprising a variety of probes, including the following: a heat probe configured to deliver controlled heat stimuli to a tooth surface and measure the heat response of the dental pulp; an electrical probe configured to deliver low-voltage electrical pulses to the tooth surface and measure the electrical impedance of the dental pulp; and an optical probe configured to assess blood oxygen saturation and microcirculation in the dental pulp using near-infrared light; a microcontroller unit configured to process sensor data from the thermal probe, the electrical probe and the optical probe, to calibrate measurements based on the oral base temperature and the ambient conditions, to aggregate multimodal sensor data and to control the operation of the thermal probe, the electrical probe and the optical probe; a cloud platform configured to receive and store aggregated sensor data, run artificial intelligence algorithms to analyze multimodal sensor data and generate diagnostic insights that include vital signs and diagnostic probabilities; a user application that is communicatively connected to the cloud platform and configured to wirelessly receive aggregated sensor data, display detailed diagnostic reports with vital signs and trends to the user, integrate with electronic health data systems, and issue alerts in case of abnormal readings; a wireless communication module connected to the microcontroller unit, configured to transmit the aggregated sensor data to the cloud platform; a display interface configured to show real-time feedback from the probes, including vitality assessments and sensor readings; and a main body containing the microcontroller unit, a rechargeable power supply and the display interface, wherein the rechargeable power supply can be charged via the current provided through a charging port on the main body, and wherein the main body is also equipped with on / off and start / stop switches; the device is configured to provide a non-invasive, quantitative real-time analysis of dental pulp health by combining physiological responses from thermal, electrical, and optical measurements.

A balanced armature receiver is disclosed including a multicoil motor located in a housing and comprising a movable armature connected to a diaphragm separating an interior of the housing into front and back volumes. The multicoil motor is electrically connected to contacts of a terminal board having an integrated capacitor component, wherein electrical connections of the multicoil motor and the capacitor component to the terminal board are configured to change an electrical impedance of the balanced armature receiver based on a frequency of an electrical signal applied to the multicoil motor.

The present invention generally relates to the field of evaluation of biological conditions of tissue and tissue samples. In particular, the present invention relates to methods and apparatus for evaluating ex vivo tissue samples in for example medical pathology, and in particular to methods and apparatus that characterizes ex vivo tissue samples using precise measurements of electrical impedance of the tissue.

To provide a technique capable of measuring a lubrication state of a rolling device when rotational operation of the rolling device is stopped.SOLUTION: A diagnostic device for diagnosing a rolling device that uses a lubricant comprises: acquisition means for acquiring the impedance and phase of the rolling device using an electrical impedance method when the rolling device starts to rotate and stops after a predetermined number of rotations; derivation means for deriving a thickness of a film derived from the lubricant on the rolling device from the impedance and the phase; and determination means for determining the lubrication state of the rolling device based on the thickness of the film.SELECTED DRAWING: Figure 2

A semiconductor package includes a substrate including a die pad, first and second discrete transistor dies mounted on the die pad, an encapsulant body that encapsulates the first and second discrete transistor dies, and a plurality of leads that are exposed from the encapsulant body, wherein the first and second discrete transistor dies are connected in parallel with one another by electrical interconnections that electrically connect common terminals of the first and second discrete transistor dies to one of the leads, and wherein at least one of the electrical interconnections has a balanced configuration that provides substantially identical electrical impedance as between the common terminals of the first and second discrete transistor dies and the lead to which they are connected.

A particulate matter detection device and a detection method, in particular, a detection device and detection method based on a dielectrophoresis and electrical impedance measurement technology is provided, and more in particular, an electrical impedance detection device utilizing a microfluidic chip, and an application thereof for detecting target particles are provided. The device comprises a sample introducing part, a main channel (3), a dielectrophoresis electric field generating part, and an electrical impedance measurement part. By using the dielectrophoresis electric field generating part to selectively control target cells, detection or counting is performed on a sample flexibly and precisely without the use of labels and antibodies.

The invention belongs to the technical field of intelligent moisture control of filter press filter plates and filter cakes, and relates to an intelligent moisture control method of a filter press filter plate and a filter cake integrated with a high-voltage-resistant electrode array. The method comprises the following steps: embedding a high-voltage-resistant electrode array into the surface of a filter plate, and detecting an electrical impedance parameter of each region in a filter cake forming process in real time; reconstructing water distribution in the filter cake in real time and generating a dynamic image by using the electrical impedance data of the plurality of groups of electrode pairs; meanwhile, establishing a mathematical model between the electrical impedance and the water content of the filter cake to obtain the real-time water content of the filter cake; and according to the moisture distribution image and the moisture content data, dynamically adjusting the parameters of the filter press through a closed-loop feedback system to realize accurate control of the moisture content of the filter cake.

The invention relates to the technical field of micro-fluidic biological detection, and discloses a micro-fluidic chip for rapidly detecting bacteria based on multi-mode detection, a preparation method and a detection method.The chip comprises a PDMS runner layer and a glass substrate layer which are sequentially arranged from top to bottom; the PDMS flow channel layer comprises an injection area used for receiving a to-be-detected sample and carrying out pretreatment; the focusing area is used for realizing three-dimensional fluid focusing of the detected particles through a coupling effect of viscoelasticity and an inertial effect; the detection area is used for performing electrical impedance detection and fluorescence detection on the focused particles; the outflow area is used for collecting and outputting the detected sample; the PDMS flow channel layer and the glass substrate layer are bonded through oxygen plasma to form a sealed channel structure, and the sealed channel structure is used for realizing electrical impedance and fluorescence dual-mode synchronous detection of microbial particles in a single flow channel. By optimizing the fluid focusing structure and the electrode design, high-precision synchronous detection of the microbial particles is realized.

The invention provides an ultrasonic scalpel amplitude-change pole design method and system based on composite structure optimization. The method comprises the steps that a performance target parameter set set during system initialization is received; dividing the amplitude-change pole into an input section, a middle transition section and an output section to construct a structure design model, and reversely optimizing the structure design model through a performance prediction module to generate a corresponding parameter set; sLM process parameters are collected, the parameter set is combined to be input into a pre-constructed error prediction module, and manufacturing error prediction is generated; real-time amplitude-change pole performance data are collected and combined, the manufacturing error prediction and the performance offset are combined, an individual final performance value is generated through Bayesian weighted fusion, and an individual performance label of each individual amplitude-change pole is constructed; the tissue electrical impedance, the cutter head temperature and the ultrasonic echo signal are collected in real time in the operation, the driving voltage of the transducer is dynamically adjusted by combining the individual performance label, and closed-loop control over the amplitude is carried out. According to the invention, a safer and more intelligent energy output scheme is provided for a high-complexity operation scene.

The present invention relates to a method and an exhaust gas sensor for determining a corrected nitrogen oxide content in the exhaust gas of an internal combustion engine. The exhaust gas sensor (10) comprises a main body (12), a measuring cavity (40) arranged in the main body (12), in which a measuring electrode (44) is arranged, an exhaust gas electrode (22) exposed to the exhaust gas, which forms an amperometric measuring cell with the measuring electrode (44), and a reference cavity (50) connected to the ambient air, in which a reference electrode (52) is arranged.The method according to the invention comprises applying a measuring current (IP2) to the measuring electrode (44) such that a measuring voltage (V2) developing between the measuring electrode (44) and the reference electrode (52) is maintained at a predetermined first setpoint value, determining a nitrogen oxide content at least partially on the basis of the measuring current (IP2) applied to the measuring electrode (44), determining the electrical impedance of the amperometric measuring cell and determining a corrected nitrogen oxide content at least partially on the basis of the determined nitrogen oxide content and at least partially on the basis of the determined electrical impedance of the amperometric measuring cell.

The invention belongs to the technical field of biological detection, and provides an electrical impedance detection system based on an FPGA (Field Programmable Gate Array), which comprises an FPGA main control board, an impedance measurement chip, a peripheral circuit of the impedance measurement chip, an RS232 serial port transmission module, a PC (Personal Computer) end upper computer and a power supply module, the power supply module supplies power to the FPGA main control board, the impedance measurement chip, the peripheral circuit of the impedance measurement chip and the PC end upper computer, the FPGA main control board is arranged between the PC end upper computer and the impedance measurement chip and the peripheral circuit of the impedance measurement chip, the impedance measurement chip is connected with the FPGA main control board through an I2C bus, and the FPGA main control board communicates with the PC end upper computer through the RS232 serial port transmission module. The electrical impedance detection system is higher in detection precision, better in stability and low in power consumption and cost, and has extremely high production and application value.

The invention discloses a piezoelectric driving micro-nano scratching instrument, and belongs to the technical field of material mechanical property detection. The scratch tester comprises a piezoelectric driving system, a multi-mode detection system and a control and data processing system. The core is that the piezoelectric driving system is completely driven by piezoelectric elements, and a displacement table adopts a clamping type stepping mechanism based on a flexible hinge, so that the combination of nanoscale motion precision and large stroke is realized; the multi-mode detection system innovatively integrates an electrical impedance detection loop composed of a conductive pressure head and a sample, can sensitively capture microscopic damage and failure behaviors of a material in the scratching process, and carries out synchronous fusion analysis with signals of a force sensor and a displacement sensor. According to the invention, the defects of insufficient precision and single detection means of the traditional scratch tester are overcome, and the accuracy and reliability of detecting the interface bonding strength and other mechanical properties of materials such as films and coatings are remarkably improved.

The invention provides a multimodal data fusion analysis method and system for pregnant and birth health. The method comprises the following steps: acquiring enhanced Raman spectrum data of amniotic fluid of a pregnant woman and electrical impedance spectrum data of blood of the pregnant woman; extracting a half-peak width parameter and a displacement parameter of a characteristic peak in a preset range from the enhanced Raman spectrum data, and analyzing a dielectric relaxation frequency variation parameter of a preset frequency band from the electrical impedance spectrum data; performing correlation analysis on the half-peak width parameter, the displacement parameter and the dielectric relaxation frequency variation parameter to construct a multi-dimensional interaction parameter; performing multi-modal data fusion analysis on the multi-dimensional interaction parameters to obtain a multi-modal data fusion analysis result including an amniotic fluid embolism probability value so as to realize risk early warning of amniotic fluid embolism; according to the multi-modal dynamic coupling and cross-scale pathological modeling, the technical barriers of data dimension limitation, static analysis lagging and multi-modal data isolation in the prior art are overcome, and an innovative technical path is provided for early accurate early warning of amniotic fluid embolism.

The invention relates to an arrangement (1) for detecting bearing parameters of a bottom bracket (10) of a bicycle (100), comprising a bottom bracket (10) which has an inner ring (11) and an outer ring (12), a voltage source (2) which is designed to generate an electrical voltage between the inner ring (11) and the outer ring (12) of the bottom bracket (10), and a detection unit (3) which is designed to detect an electrical impedance between the inner ring (11) and the outer ring (12) of the bottom bracket (10) at at least two detection positions (5) distributed around the circumference of the bottom bracket (10), wherein the detection unit (3) is designed to determine at least one predetermined bearing parameter based on at least two electrical impedances at different detection positions (5).

The invention discloses a tumor single cell identification method based on a residual network, a microfluidic device and microfluidic equipment, and relates to the technical field of microfluidics, the method comprises the following steps: adopting an impedance flow cytometry method to obtain an initial electrical response signal, and then obtaining an electrical impedance signal corresponding to each frequency point through a lock-in amplifier; normalizing the electrical impedance signal of each frequency point, converting the normalized electrical impedance signal into a grey-scale map, and splicing the grey-scale maps of the corresponding frequency points at the same moment to obtain a two-dimensional image feature; constructing a residual network, correspondingly reducing the scale of a residual structure according to the two-dimensional image features, and training the network by using a data set marked with various cell categories; and according to an electrical response signal measured in real time, converting the electrical response signal into a two-dimensional image feature, and inputting the two-dimensional image feature into the trained residual network to obtain the category of the tumor cells. According to the method, the overfitting problem and the network model degradation problem which are easily caused when the impedance peak value is singly used as the input feature to be input into the full-connection neural network for cell classification in the prior art are solved.

The invention provides a breast cancer tissue anomaly detection method based on multi-frequency electrical impedance dynamic analysis, and the method comprises the steps: generating a multi-frequency electrical excitation signal covering a preset low frequency to a high frequency, applying the multi-frequency electrical excitation signal to a to-be-detected breast tissue through an electrode array, and synchronously collecting a response voltage signal. Orthogonal demodulation is carried out on the collected voltage signals, real and imaginary components of each frequency point are separated, a complex impedance value is calculated, and a multi-frequency impedance spectrum is generated. Feature vectors including amplitude-frequency characteristic slope, phase-frequency characteristic extreme point position, high-frequency-band impedance attenuation rate and the like are extracted from the impedance spectrum, a pre-trained dynamic judgment model is input to calculate a tissue anomaly index, and finally whether the mammary gland tissue is abnormal or not is judged according to a comparison result of the anomaly index and a preset threshold value. The accuracy of early detection of breast cancer can be improved, and the stability and reliability of detection are enhanced.

The invention discloses a non-inductive operation quality tracing method in the glass fiber industry, which relates to the technical field of glass fiber quality tracing and comprises the following steps of: selecting a PZT sensor for installation, acquiring acquired data in cooperation with an analog-to-digital converter, respectively calculating impedance values in a low-frequency interval and a high-frequency interval and identifying characteristics, calculating a signal-to-noise ratio to confirm and identify characteristic frequency points, and analyzing the change rate of the adjacent identification characteristic frequency points. According to the method disclosed by the invention, the impedance of the glass fiber epoxy plate is finely measured at low frequency and high frequency, and calculation and analysis of a signal-to-noise ratio are combined, so that high-sensitivity detection of the internal structure and defects of the material is achieved, and possible damage of the glass fiber epoxy plate in the actual use process can be simulated by artificially introducing bonding defects, so that the detection accuracy is improved. And impedance data of the material in different damage states can be collected, and tiny changes in the material can be detected in real time by monitoring the electrical impedance value of the glass fiber epoxy plate at the key frequency point in real time, so that early damage identification is realized.

Described herein is an implantable device configured to detect impedance characteristic of a tissue. In certain exemplary devices, the implantable device comprises (a) an ultrasonic transducer configured to emit an ultrasonic backscatter encoding information relating to an impedance characteristic of a tissue based on a modulated current flowing through the ultrasonic transducer; (b) an integrated circuit comprising (i) a variable frequency power supply electrically connected to a first electrode and a second electrode; (ii) a signal detector configured to detect an impedance, voltage, or current in a circuit comprising the variable frequency power supply, the first electrode, the second electrode, and the tissue; and (iii) a modulation circuit configured to modulate the current flowing through the ultrasonic transducer based on the detected impedance, voltage, or current; and the first electrode and the second electrode configured to be implanted into the tissue in electrical connection with each other through the tissue. Further described are systems including one or more implantable devices and an interrogator for operating the implantable device, methods of measuring impedance characteristic of a tissue in a subject, and methods of monitoring or characterizing a tissue in a subject.

A modular waterproof therapeutic electrode component for preventing water ingress and for easy servicing. The component comprises a substrate comprising a conductive surface, a reservoir of conductive fluid mounted on the substrate, a reusable waterproof enclosure comprising circuitry, the reusable waterproof enclosure comprising circuitry configured to be removably coupled to the substrate, and a fluid deployment device in electrical communication with the circuitry and mounted on the substrate, the fluid deployment device configured to cause the reservoir to release the conductive fluid onto the conductive surface to reduce electrical impedance between the conductive surface and skin of a subject.