Monitoring system

Abstract

A method for estimating blood pressure comprises, at a processor of a sensor system comprising a plurality of bio sensors, receiving signals from the plurality of bio sensors, processing the received signals, and generating a blood-pressure estimate. The received signals are processed to determine a photoplethysmography Pulse Arrival Time (PAT(PPG)) and a bioimpedance Pulse Arrival Time (PAT(BioZ)). Generating the blood-pressure estimate is based on a combination of the determined PAT(PPG) and the determined PAT(BioZ), so that pre-ejection period (PEP) variability is compensated for. The received signals include electrocardiography (ECG) signals, bioimpedance (BioZ) signals, and / or optical photoplethysmography (PPG) signals.

Description

Monitoring SystemTechnical Field

[0001] The present disclosure broadly relates to health monitoring systems and, more particularly, to a health monitoring device having multiple medical sensors.Background

[0002] Vitals signs form a cornerstone of the diagnosis, management, and monitoring of many health conditions. Diagnostic vital signs monitoring outside the hospital environment is tedious, complex, and difficult to perform with accuracy and consistency without a trained healthcare professional in attendance.

[0003] Patients in hospitals often need their vital signs to be measured frequently. This can be disruptive to the patient, is time consuming, time inefficient, and labour intensive for the clinical healthcare provider to perform. Furthermore, the complexity and expense of automated monitoring equipment precludes its widespread use for all patients.

[0004] Any discussion of documents, acts, materials, devices, articles or the like which has been included in the present specification is not to be taken as an admission that any or all of these matters form part of the prior art base or were common general knowledge in the field relevant to the present disclosure as it existed before the priority date of each claim of this application.Summary

[0005] The pre-ejection period (PEP) can significantly impact the accuracy of blood pressure (BP) measurements, especially when using cuffless devices that rely on pulse transit time (PTT) and pulse arrival time (PAT). PEP is a variable electromechanical delay between the electrical activation of the heart and the opening of the aortic valve, and it can change due to factors like stress, physical activity, heart rate, and age. If PEPis not accounted for, it can introduce considerable measurement uncertainties, limiting the accuracy of BP estimation. The device and methods described herein provide a solution to this problem, by taking the variability of PEP into account and reducing its impact.

[0006] In one aspect there is provided a monitoring device for monitoring a patient’s health indicators, the monitoring device comprising: a sensor unit comprising: one or more medical sensors having one or more sensor electrodes; a controller for directing operation of the monitoring device; and a communications module for communicating with a user terminal; and an applicator adapted to provide an interface between the monitoring device and a patient so that the sensor electrodes make contact with the patient.

[0007] The monitoring device may comprise an internal housing configured to house the sensor unit; and an external housing configured to house the internal housing with the sensor unit, wherein the applicator is removably adhered to an underside of the external housing.

[0008] The external housing may be flexible and have a flexible contact surface, and the applicator may comprise an adhesive and be removably adhered to the flexible contact surface.

[0009] The applicator may comprise a flexible base layer and a plurality of conducting tracks carried by the base layer; a first side of the applicator adapted to be connectable to the device via a first adhesive layer; a second, opposite side of the applicator adapted for placement on a patient; and the applicator may be adapted to match the external housing in shape and size thereby securely attaching the external housing to the patient. In some embodiments the applicator may be adapted to approximate and / or be larger than the external housing to thereby be configured to securely attach the external housing to the patient.

[0010] The applicator may be adapted so that the conducting tracks are in conductive communication with electrode points on the internal housing, thereby conductively connecting the internal electrode points to the external electrodes on the applicator.

[0011] The external housing and the applicator may be adapted in shape and size to be applied across a patient’s chest in a variety of shapes and sizes, with the applicator adapted to provide electrodes within a shoulder region for patient monitoring. In some embodiments, the applicator may be adapted in shape and size to be applied across a patient’s chest from shoulder to shoulder

[0012] The monitoring device may comprise a power supply comprising: a rechargeable battery and a charging interface; and an isolation system configured to disconnect the charging interface from the rechargeable battery while the monitoring device is in use for monitoring a patient’s health.

[0013] The communications module may comprise a data interface; the charging interface and the data interface may be a shared interface; and the isolation system may be configured to disconnect the rechargeable battery from the charging interface while the data interface is in use for uploading and / or downloading monitoring data.

[0014] The one or more medical sensors may comprise a blood pressure sensor system comprising: a plurality of sensors comprising an optical sensor, a bioimpedance sensor, and an ECG sensor; a processing module in data communication with the plurality of sensors, wherein the processing module is configured to: process received signals from the plurality of sensors; and determine a blood pressure estimate based on one or more of: a. a pulse transit time (PTT); b. a pre-ejection period (PEP); c. a pulse arrival time (PAT); d. a heart rate (HR); e. a heart rate variability (HRV);f. an ECG measure; g. a bioimpedance measure; and h. a photoplethysmography measure.

[0015] Bioimpedance is generally referred to as “BioZ” herein, but may also be referred to as “BioImp”.

[0016] The processing module may be configured to determine the blood pressure estimate according to an algorithm, as described by one of:(I) BP Estimate = a*PAT (PPG or BioZ) + C *HRV +d.; or(II) BP Estimate = a *PA TPPG+ b *PA TBIO z+c; or(III) BP Estimate = a*PAT (ppG orBioz)+c.

[0017] In another aspect there is provided a monitoring system for monitoring a patient’s health indicators, the system comprising a user terminal; and a monitoring device (as described), in communication with the user terminal.

[0018] In another aspect there is provided physiological monitoring system comprising: a plurality of bio sensors; at least one processor coupled to the plurality of bio sensors, wherein the at least one processor is configured to: receive signals from the plurality of bio sensors; process the received signals to determine a photoplethysmography Pulse Arrival Time (PAT(PPG)) and a bioimpedance Pulse Arrival Time (PAT(BioZ)); and generate a blood-pressure estimate based on a combination of the determined PAT(PPG) and the determined PAT(BioZ) that compensates for pre-ejection period (PEP) variability.

[0019] The plurality of bio sensors may comprise one or more of: an electrocardiography (ECG) sensor; a bioimpedance (BioZ) sensor; and / or an optical photoplethysmography (PPG) sensor.

[0020] The at least one processor may be configured to estimate and continuously correct inter-channel delay and drift by updating per-channel offset parameters basedon one or more of: cross-correlation between ECG and BioZ landmarks, similarity measures between landmark sequences, beat matching constrained by R-R intervals, and / or a calibration offset.

[0021] In another aspect, a method for estimating blood pressure comprises: at a processor of a sensor system comprising a plurality of bio sensors: receiving signals from the plurality of bio sensors; processing the received signals to determine a photoplethysmography Pulse Arrival Time (PAT(PPG)) and a bioimpedance Pulse Arrival Time (PAT(BioZ)); and generating a blood-pressure estimate based on a combination of the determined PAT(PPG) and the determined PAT(BioZ) that compensates for pre-ejection period (PEP) variability.

[0022] Receiving signals from the plurality of bio sensors may comprise receiving one or more of: electrocardiography (ECG) signals, bioimpedance (BioZ) signals, and / or optical photoplethysmography (PPG) signals.

[0023] The method may comprise estimating and continuously correcting interchannel delay and drift by updating per-channel offset parameters based on one or more of: cross-correlation between ECG and BioZ landmarks, similarity measures between landmark sequences, beat matching constrained by R-R intervals, and / or a calibration offset.

[0024] The method may comprise determining a pre-ejection period (PEP) from an interval between an ECG fiducial and a BioZ mechanical fiducial.

[0025] Receiving signals from the plurality of bio sensors may comprise acquiring, in a time-aligned manner, ECG, BioZ and PPG signals from a subject. Acquiring the ECG, BioZ and PPG signals from a subject may be synchronised.

[0026] Processing the received signals to determine the PAT(PPG) and the PAT(BioZ) may comprise: detecting an ECG fiducial corresponding to ventriculardepolarization; detecting a BioZ fiducial corresponding to aortic valve opening; and detecting a PPG fiducial corresponding to a peripheral pulse landmark.

[0027] Processing the received signals may comprise: computing PAT(PPG) between an ECG fiducial and a PPG fiducial; and computing PAT(BioZ) between the ECG fiducial and a BioZ fiducial.

[0028] Generating the blood-pressure estimate may take into consideration a preejection period (PEP) that is a time interval between an ECG fiducial and a BioZ mechanical fiducial.

[0029] Generating the blood pressure estimate may comprise combining PAT(PPG) and PAT (BioZ) according to a parameterized model described by: BP Estimate = a *PA T(PPG) + b *PA T(BioZ) + c .

[0030] Coefficients a and b may be obtained via calibration, for example via an initial calibration step.

[0031] The blood pressure estimate may be generated based on one or more of: age; height; BMI; a heart rate (HR); and / or a heart rate variability (HRV).

[0032] The method may be used for cuffless blood-pressure estimation.

[0033] Throughout this specification the word “comprise” or variations such as “comprises” or “comprising”, will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps.Brief Description of Drawings

[0034] Embodiments of the disclosure are now described by way of example with reference to the accompanying drawings in which:

[0035] Figure 1 is a schematic representation of an embodiment of a monitoring system.

[0036] Figure 2 is a block diagram of an embodiment of a monitoring device.

[0037] Figure 3 is a block diagram of an embodiment of a computing device.

[0038] Figure 4 is a block diagram of an embodiment of a monitoring device.

[0039] Figure 5 is an exploded view of an embodiment of a monitoring device.

[0040] Figures 6A and 6B are a bottom and top exploded view, respectively, of another embodiment of a monitoring device.

[0041] Figure 7 is a schematic representation of another embodiment of a monitoring system.

[0042] Figure 8 is a schematic representation of the signal processing applied to the acquired sensor signals.

[0043] Figure 9 illustrates an example of an ECG measurement and related PAT calculations for PPG or bioimpedance.

[0044] Figure 10 is a flow diagram of a charge disconnection algorithm.

[0045] In the drawings, like reference numerals designate similar parts.Detailed Description

[0046] Described herein is a monitoring system that includes a monitoring device (e.g., in the form of a patch) that is applied to a patient’s body, and may be used to monitor several indicators associated with a patient’s condition, such as vital signs, including one or more of heart rate, heart rhythm (e.g., ECG), respiratory rate, oxygensaturation, temperature, blood pressure, and heart rate variability. The monitoring device may be used to monitor non-vital indicators such as patient posture and / or activity. The device is applied to a person’s body, for example on a patient’s chest.

[0047] Figure 1 of the drawings shows a monitoring system 100 for monitoring a person’s health indicators. The system may be used, for example, for monitoring vital signs by taking clinical measurements including body temperature, pulse rate, respiration rate, and / or blood pressure. The monitoring system 100 includes a monitoring device 120 in communication with a user terminal 130 via a communication connection or network 110. In some embodiments, the monitoring system 100 may also include a monitoring platform 102, for example in the form of a computing device in communication with one or more user terminals 130 via the communication network 110.

[0048] As shown in Figure 2 of the drawings, the monitoring device 120 includes a sensor array 122 having one or more sensors 124. The sensors 124 may include one or more of the following: a heart rate sensor, a heart rhythm sensor, a respiratory rate sensor, an oxygen saturation sensor, a temperature sensor, and / or a blood pressure sensor. Each sensor is adapted to sense at least one body function characteristic of the person (e.g. a patient), such as pulse rate. The monitoring device 120 includes a processor 126, and each sensor is configured to output a sensor signal to the processor 126, the sensor signal indicative of that sensor’s sensed body function. The monitoring device 120 includes a communication module 128, and the processor 126 is configured to output the various sensor signals to a connected user terminal 130 via the communication module 128 and the communication network 110. The monitoring device 120 also includes a power supply 129.

[0049] In some embodiments the device 120 may include memory 127 configured for data caching and thereby providing a backup, e.g., for when the device is not connected to the network or to a user terminal.

[0050] The communication module 128 may be configured for wired and / or wireless connection. Physiologic data transmission from the monitoring device to the user terminal via the communication network may be via one or more wireless communication protocols / networks, e.g. Bluetooth (BLE), Wi-Fi, 5G etc. The communication module 128 is configured to allow switching between BLE and / or WiFi (in some embodiments with a preference for BLE to preserve battery life).

[0051] In some embodiments, the use of BLE and / or Wi-Fi in the device may allow access to real time location services (RTLS), i.e. knowing where the patient is in the hospital at all times. In some embodiments, the RTLS may be used to automate alerts and location, for example should the patient fall or have a cardiac arrest.

[0052] Some embodiments may include a gateway receiving device that can receive the BLE and / or Wi-Fi signal and forward the information on to a server or the cloud, for example to a monitoring platform 102. The monitoring platform 102 may, for example, track and log patient health, and / or provide remote access to monitoring information for health care providers and / or patients.Sensors

[0053] One or more sensors are included in the sensor unit to measure one or more of a. Heart rate b. Heart rhythm (with single and / or multi lead ECG) c. Respiratory rate (bioimpedance, ECG) d. Blood pressure (ECG, red and green photoplethysmography (PPG) and bioimpedance (BioZ)) e. Oxygenation (PPG) f. Temperature (skin infrared) g. Inertia measurement unit (IMU) (indicating posture and activity).

[0054] The measurement of blood pressure (BP) may be realised through a combination of photoplethysmography (PPG), bioimpedance (BioZ), and Electrocardiogram (ECG) to improve accuracy.

[0055] The PPG may be measured using multiple wavelengths. The switching of two types of PPG (red and green wavelength) is applied and the measurement is carried out for both types. As described in more detail elsewhere herein, a BP algorithm is used to calculate systolic and diastolic BP values from pulse transit or pulse arrival times obtained from a combination of PPG, Bio, and ECG signals. For example, the PPG is combined with the BioZ to determine Pulse Transit Time (PTT), and ECG is combined with BioZ to determine Pulse Arrival Time (PAT).

[0056] The blood pressure sensors may be provided by a combination of PPG, ECG, and BioZ. The device may be configured to utilise a combination of PPG, ECG, BioZ and IMU to determine the blood pressure.

[0057] In some embodiments, the blood pressure may be estimated from obtained measurements. The estimation may be performed by the monitoring device, the monitoring application program on the user terminal, and / or a monitoring application at the monitoring server or in the cloud (i.e., servers and associated software and databases accessed over the internet).

[0058] In some embodiments the estimation may be based on a measured ECG signal, pulse wave velocity (PWV), and PAT as described in international patent application PCT / AU2016 / 050803, incorporated herein in its entirety by reference.

[0059] In some embodiments the estimation may be performed as described in Pour Ebrahim, M., Heydari, F., Wu, T. et al. Blood Pressure Estimation Using On-body Continuous Wave Radar and Photoplethysmogram in Various Posture and Exercise Conditions. Sci Rep 9, 16346 (2019), incorporated herein in its entirety by reference.

[0060] In some embodiments the estimation may be performed as described in Heydari F, P. Ebrahim M, Redoute J-M, et al. Clinical study of a chest-based cuffless blood pressure monitoring system. Med Devices Sens. 2020; 3:el0091, incorporated herein in its entirety by reference.

[0061] In some embodiments the estimation may be performed as described in F. Heydari et al., "Continuous Cuffless Blood Pressure Measurement Using Body Sensors," 2018 IEEE SENSORS, New Delhi, India, 2018, pp. 1-4, doi:10.1109 / ICSENS.2018.8630294, incorporated herein in its entirety by reference.

[0062] In some embodiments the estimation may be performed as described in Heydari, F. et al. (2020). Cuffless Blood Pressure Estimation Based on Pulse Arrival Time Using Bioimpedance During Different Postures and Physical Exercises. In: Sugimoto, C., Farhadi, H., Hamalainen, M. (eds) 13th EAI International Conference on Body Area Networks . BODYNETS 2018. EAVSpringer Innovations in Communication and Computing. Springer, Cham, incorporated herein in its entirety by reference.

[0063] The measurement of the respiratory rate may be realised through bioimpedance (BioZ) to improve accuracy from interference.

[0064] The measurement of the vital signs can be performed by the monitoring device when the user is active and / or moving. The interference of sensor signals which may be caused by movement, muscle tension, and connection issues are mitigated by the combination of PPG, BioZ, and ECG measurements. Mitigation may involve, for example, identifying an anomaly in one signal, and searching for a correlation in other signals. Any anomalies identified can then be removing using one or more hardware and / or software filters. In some embodiments, the relevant filter bandwidths are adapted based on the identified anomalies, thereby eliminating or reducing movement related signal corruptions. The anomalies due to, for example, movement of the patient, are usually low frequency signals imposed on the actual vital signs, and can therefore be eliminated by filtering once the low frequency of the movement is determined.

[0065] Advantageously, the sensor unit is able to associate measured parameters with one another. The ability to associate measured parameters provides new insights that have not been able to be obtained in the past. For example, the combination of measuring the heart rate, heart rhythm, blood pressure and posture simultaneously, in real time, at home or in the hospital, and during patient activity may be used in the investigation and / or management of dizziness, falls, postural hypotension, autonomic dysfunction and other medical conditions. This has previously not been possible.

[0066] There are many other combinations of measurement parameters similar to the above that can provide new insights as to what is happening.

[0067] Sensor operation may be configurable via the user terminal. For example: a. One or more sensors may be turned on or off by a monitoring application program if not required, thereby saving battery power. b. The frequency of any vital sign measured can be set via the monitoring application. c. Standard combinations of vital sign parameters can be set to happen e.g. routine ward vital signs, post operative vital signs, important vital signs to monitor in a condition such as acute asthma exacerbation. d. Favourite combinations of vital signs measured can be saved by a user. e. The user can set the monitoring device to measure a vital sign more frequently if an abnormality is detected, e.g. if the respiratory rate is set to be measured every hour and an abnormal value is detected, then the respiratory rate will be measured every 5 minutes for the next hour. f. If an abnormal vital sign is detected, the monitoring device can be set up to monitor other relevant vital signs automatically. g. When an abnormal vital sign (or a combination of them) is detected, the monitoring application is able to escalate by the way of an alert communicated to the user or clinical healthcare provider. h. The monitoring application supports ‘smart alarms’ e.g. if a single vital sign is abnormal but all other vital signs remain the same, then adecision support process determines whether the alarm should notify the user or healthcare provider or not. i. Deterioration scores can be calculated by the monitoring application and management of the patient’s condition can be escalated if thresholds are reached.Blood Pressure Measurement

[0068] The monitoring system and monitoring device described herein are used to collect the user’s vital signs. Multiple vital signs can be collected simultaneously, including heart rate, ECG, respiratory rate, oxygen level, temperature, and blood pressure. Some embodiments support wireless communication, for example using Bluetooth low energy (BLE), between the monitoring device and a monitoring platform. This is illustrated in Figure 7 of the drawings, which shows an embodiments of a monitoring system 700 for monitoring a person’s health indicators. The monitoring system 700 includes a monitoring device 720 in communication with a user terminal 730 via a communication connection or network 710. In some embodiments, the monitoring system 700 may also include a monitoring platform 702, for example in the form of a computing device in communication with one or more user terminals 730 via a communication network 712.

[0069] In the exemplary embodiment of Figure 7, the monitoring device 720 includes multiple sensors 721 in communication with a processor 722 (for example a microcontroller), memory and / or storage 723 connected to the processor, a battery with associated power management 724 for powering the device. In some embodiments the device may have a wireless charging interface 725. The monitoring device 720 also includes a communications interface 726 (for example including BLE, NFC, and / or USB interfaces).

[0070] Harnessing the power of multiple signals in real time represents a paradigm shift towards more accurate and effective patient assessment and monitoring. Traditionally, reliance on a limited number of signals has been the norm, but embracinga multifaceted approach promises unparalleled benefits with respect to measurement insights.

[0071] The monitoring device described herein is able to utilise multiple sensors, including optical sensors (green and red), bioimpedance sensors, an ECG sensor, temperature sensors, and / or an accelerometer.

[0072] In some embodiments, the sensor optical signals, bioimpedance signal, and ECG signal are used to calculate blood pressure (BP). Conventionally, cuffless digital BP is calculated using the principles of pulse transit time (PTT) or pulse arrival time (PAT), from two pulses obtained at two locations on the body. For example, an optical sensor can detect a PPG signal, and when used in combination with an ECG, a pulse arrival time can be calculated between the ECG signal, which is the start of the pulse at the heart, and the PPG signal, which is the arrival of the pulse at another location on the body (e.g., a finger, a chest, etc.). The BP can then be determine based on the correlation between PAT and BP; for example, BP = aPAT + b. The coefficients a and b are obtained through some initial calibration for an accurate continuous BP measurement.

[0073] Referring to Figure 8 of the drawings, the recorded raw signals are received at 810 (ECG, BImp, and PPG) and then undergo signal pre-processing at 820. The signals are filtered, using a bandpass filter (BPF) to eliminate the effects of respiration, 50 Hz power line noise, and / or motion artifacts etc. The BPF is designed to remove any DC offset, low frequency and high-frequency noise sources. The pass and stop frequencies are calculated based on heart rate frequency (HRF) as described in Fatemeh Heydari, Malikeh P. Ebrahim, Jean-Michel Redoute, Keith Joe, Katie Walker, Mehmet Rasit Yuce, A chest-based continuous cuffless blood pressure method: Estimation and evaluation using multiple body sensors, Information Fusion, Volume 54, 2020, Pages 119-127, (‘Fatemeh Heydari’) incorporated herein by reference. In some embodiments, the HRF may be calculated using one of the signals that is affected the least from the effect of motion and respiration.

[0074] Following pre-processing 820, the PAT / PTT is calculated at 830. For this, a peak detection algorithm may first be used to detect ECG peaks, rise time (tr), minimum. In some embodiments maximum features from bioimpedance (BioZ) and / or PPG signals may be detected to determine the PAT. In some embodiments, other timings of the features of the three acquired signals are considered, such as derivatives. A calibration input 840 is then utilised when calculating the blood pressure (SBP / DBP) at 850.

[0075] Figure 9 illustrates an example of an ECG measurement 910 and related PAT calculations for PPG or bioimpedance 920.

[0076] The ECG R-peak at tp is detected using the Pan-Tompkins algorithm or a similar algorithm, for example as defined in Fatemeh Heydari. Moving average filtering may be applied to the PAT and / or the PTT to reduce the noise and / or outliers for better accuracy. This may be understood with reference to the following equations:PAT = tr-tp = tmax-tp (1)SBPest = PAT*al+cl (2)DBPest = PAT *a2 +c2 (3) where SBP: Systolic Blood Pressure and DBP: Diastolic Blood Pressure.

[0077] In the estimation above, heart rate (HR) and heart rate variability (HRV) are considered. Heart Rate Variability (HRV) is influenced by a diverse array of factors spanning physiological, pathological, psychological, lifestyle, environmental, stress, anxiety and genetic realms. Other influencers may include metabolic diseases e.g. diabetes, lung diseases e.g. chronic obstructive pulmonary disease (COPD), kidney disease, and diseases of the nervous system. Taking HRV into account enables a better and more accurate BP estimate for people with those conditions.

[0078] Accordingly, one improved algorithm is as shown here:BP Estimate = a *PAT(BiozorPPG) + c *HRV+d (model I)

[0079] Another improved algorithm that uses a combination of BioZ and PPG is as shown here:BP Estimate = a *PA Tpp b *PA T BiOz+ c ( model II)

[0080] Another alternative algorithm that may be used is as shown here:BP Estimate = a *PA T (BIOZ or PPG) +c (model III)

[0081] In Model I, age, HR and / or BMI may be taken into consideration with HRV, for example BP Estimate= a *PAT(BiozorPPG) + b *HR +c *HRV+d .

[0082] Age, HR and / or BMI may be taken into consideration with HRV in Model II and / or Model III

[0083] Model II uses a combination of BioZ and PPG, thereby improving accuracy by separating the timing changes due to PEP from the timing changes due to arterial PTT.

[0084] The Pulse Arrival Time (PAT) is calculated as the sum of the Pulse Transit Time (PTT) and the Pre-ejection Period (PEP): PAT=PTT+PEP. The pre-ejection period (PEP) can be measured from the PATs obtained from combination of three biosignals: ECG, BioZ and PPG signals.

[0085] PEP is the electromechanical delay from the ECG onset to the BioZ / ICG B- point (aortic valve opening). PEP is determined by the delay in ventricular electromechanical activity and the isovolumic contraction phase, and can fluctuate based on contractility and afterload, often comprising a significant portion of PTT. Consequently, PAT may not serve as an adequate substitute for PTT in reflecting BP levels. Pre-ejection Period (PEP) and Vascular Transit Time (VTT) are components of the Pulse Transit Time (PTT). PEP is the time from electrical heart activation (ECG R- wave) to aortic valve opening, and VTT is the time it takes for the pulse wave to travel from the heart to a distal location after the valve opens. Therefore, PTT is the total time for the pulse wave to travel from its origin in the heart to a peripheral location, and it is represented as PTT = PEP + VTT.

[0086] Usually, the Pre-ejection Period (PEP) is assessed through pulsed Doppler echocardiography (ECHO).

[0087] PEP can be determined by finding an electrical start on the ECG and a mechanical start on the BioZ / ICG, then taking the time difference. PEP can be measured from the combination of three biosignals, ECG, BioZ, and PPG. The ECG provides the electrical fiducial and the BioZ provides the mechanical fiducial. This method may therefore be implemented by measuring the interval between the B-point of the impedance cardiogram (ICG) (indicating aortic valve opening) and the onset of the Q-wave on the electrocardiogram (ECG). PPG is acquired alongside these signals for the PAT terms used in the BP model, while PEP itself is derived from the ECG- BioZ pairing.

[0088] The term “fiducial” refers to a fixed basis of comparison. As used herein, a fiducial is a consistently and objectively identifiable feature of a physiological waveform that serves as a reference for measurement (e.g., timing or amplitude). Examples include the ECG QRS onset or R-peak; the BioZ / ICG B-point (aortic valve opening) or dZ / dt maximum; and the PPG foot, maximum upstroke (slope) point, or systolic peak. A fiducial time is the timestamp assigned to such a feature after signal preprocessing; a fiducial pair denotes two fiducials (optionally from different signals) used to compute an interval (e.g., PEP or PAT). Fiducials may be detected by thresholding, derivative / zero-crossing tests, matched filtering, template matching, or machine-learned classifiers, optionally within tolerance windows to improve robustness.

[0089] Distinctively, the monitoring system employs algorithms that explicitly define pulse arrival time (PAT) as the sum of pulse transit time (PTT) and the pre-ejection period (PEP) , deriving PEP from the joint analysis of ECG, bioimpedance (BioZ) and PPG signals; blood-pressure estimation then uses formulations that (i) treat PAT landmarks from PPG and BioZ as separate terms and (ii) incorporate heart-rate variability (HRV) (optionally with HR / age / BMI) to adapt the estimate to autonomic and physiological state. By modelling PEP explicitly (rather than assuming PATapproximates PTT) the device compensates for contractility- and afterload-driven variability in PEP, delivering more robust, calibration-efficient, and clinically meaningful cuffless blood-pressure tracking across postures and motion.

[0090] Considering existing solutions from the prior art, it would be counterintuitive to add BioZ and then use the tri-synchronous ECG-PPG-BioZ stack to compute BP from PAT / PTT, because the prevailing art teaches the opposite direction: most cuffless methods treat PAT as a surrogate for PTT and either ignore, assume constant, or crudely regress out PEP, while wearable BioZ is typically exploited for respiration, fluid status, or stroke-volume trends rather than precise electromechanical timing. Making BioZ the mechanical clock that exposes aortic valve opening (B-point) so PEP can be measured and subtracted has therefore involved non-trivial co-design of hardware and algorithms: electrode geometry and drive / readout to obtain stable cardiac impedance in a compact device; sub-millisecond cross-channel synchronization of ECG R-peaks, BioZ dZ / dt landmarks, and PPG foot despite different sensor bandwidths, latencies, and motion artifacts; and robust segmentation / HRV-informed modelling so the separated PTT maps to BP across postures and autonomic states. Absent these coordinated solutions, simply “adding BioZ” tends to amplify timing noise and drift, not accuracy, and the extra power / complexity would have discouraged inclusion. The synchronized three-signal architecture and PEP-explicit algorithms described herein therefore run counter to common assumptions, overcome multiple integration barriers, and deliver an accuracy gain that the prior art neither suggested nor enabled.

[0091] In certain embodiments, the monitoring system integrates bioimpedance (BioZ) with photoplethysmography (PPG) and electrocardiography (ECG) in a time- synchronized architecture. This configuration provides concrete technical advantages over optical-only arrangements: BioZ supplies a mechanical timing marker associated with aortic valve opening, enabling explicit detection of the pre-ejection period (PEP); PEP can then be modelled and removed from pulse-arrival measurements so that the remaining transit component maps more accurately to blood pressure. The concurrent use of ECG, PPG and BioZ further enhances signal fidelity by leveraging complementary sensing physics (electrical, optical and mechanical), improvinglandmark detectability across posture, motion and autonomic variation. The device implementation, including safe, comfortable electrode geometry and sub-millisecond cross-channel synchronization, supports reliable extraction and fusion of ECG, PPG and BioZ features, yielding more stable PAT / PTT-based blood-pressure estimation than approaches that rely on PPG (with or without ECG) or that apply BioZ only to unrelated parameters such as hydration or respiration.

[0092] The system applies a time-synchronized tri-sensor architecture (ECG + PPG + BioZ) that uses BioZ as a mechanical fiducial to explicitly measure PEP and then combines PAT from PPG and from BioZ to estimate blood pressure (with PAT defined as PTT+PEP). This BioZ-based PEP handling, rather than assuming or ignoring PEP, improves the accuracy of the results.

[0093] Notably, the raw ECG, BioZ and PPG signals are recorded together and then jointly pre-processed, after which the algorithm detects ECG peaks and timing features in the BioZ / PPG streams to compute intervals, i.e., PAT defined as PAT = tr-tp = tmax- tp. Computing the cross-signal intervals uses a common time base. The optical, bioimpedance and ECG signals are used together to calculate BP, and the algorithms used combine PAT(PPG) and PAT(BioZ), and derive PEP from the combination of the three biosignals; this involves time-aligned acquisition across the channels.

[0094] In embodiments where the ECG, PPG, and BioZ channels are acquired on a common time base, or are provided with precise timestamps that allow post-hoc alignment, the processors operate on time-aligned samples. Time alignment ensures that intervals such as the pre-ejection period (ECG R-peak to BioZ aortic-valve opening) and pulse-arrival times (ECG R-peak to PPG / BioZ landmarks) are computed within the same cardiac cycle, minimizing clock skew, latency jitter, and beatmismatch errors. This alignment materially improves the stability and accuracy of the PAT / PTT-based blood-pressure estimate and enables consistent fusion of PAT(PPG) and PAT(BioZ) within the disclosed models.

[0095] In some embodiments, synchronisation is not strictly used. In these embodiments, the system will (i) estimate and continuously correct inter-channel delay and drift in software (e.g., by cross-correlating ECG-BioZ landmarks, matching beats via R-R intervals, or using a one-time calibration offset), (ii) compute features that are robust to small misalignments (e.g., using tolerance windows for PEP and PAT detection), and (iii) use BioZ not only as a timing fiducial but also as auxiliary mechanical covariates (e.g., dZ / dt morphology, B-point confidence, respiration phase) in the BP model. These embodiments still leverage the distinctive tri-modal fusion and the explicit treatment of PEP in PAT / PTT-based estimation.

[0096] Embodiments incorporating time alignment or synchronisation improve precision and stabilityUser Terminal

[0097] Figure 3 is a block diagram of an example embodiment of a computing device that forms part of a user terminal 130. Each user terminal 130 includes a processor 310, storage 320, memory 330, and a communication interface 340 for communicating with external entities. The various components of the user terminal 130 are interconnected via a bus 350. This configuration may be implemented using a bespoke computing device, or in some embodiments standard devices such as a mobile phone, table or laptop may be used.

[0098] The user terminal runs a monitoring application program that allows a user to access, view, track, display, download, print, etc., monitor data. For example, the application program may display monitored vital signs such as blood pressure and temperature that the user can view on the display of the computing device.

[0099] In some embodiments, the monitoring application program may use an application programming interface (API) to communicate with and obtain data from the device. In some embodiments the monitored data may be transmitted using a Fast Healthcare Interoperability Resources (FHIR) standard, for example FiHR HL7.

[0100] Because of the simplicity of the application of the monitoring device described herein, the device may be used by a patient for home monitoring. In this type of application, the patient is able to use a personal computing device such as a mobile phone, tablet or laptop as a user terminal. The monitoring device can be paired with the patient’s computing device via an available communication network (for example via USB, BLE, Wi-Fi and / or NFC), and identification of the monitoring device is via the UID (retrieved via, e.g. a QR code printed on the device). The patient is able to view, download, save, print, and / or share the monitoring data, i.e., the monitored health indicators.

[0101] For hospital use, staff are able to access the monitor data via, e.g., a desktop computer, mobile device logged in to the staff member’s profile, and / or a mobile device that identifies the patient at the bedside and the device worn by the patient via the patient’s ID wristband, NFC or BLE proximity (with the advantage of allowing many authorised healthcare providers to access information quickly and easily at the patient bedside).

[0102] After the monitoring device is applied to the patient’s chest, the application program will confirm that that there is adequate contact of the electrodes with the body, and that other sensors, e.g. temperature or PPG, have adequate signal quality. These notifications are output based on data communicated to the user terminal from the monitoring device via the communication network.

[0103] For hospital use, when placing the monitoring device on a new patient, the device registration process may include associating relevant identifiers via the application program. For example, a patient identifier (e.g., as provided on a hospital ID wristband), a monitoring device UID (as accessed via printed UID, QR code, or NFC), and / or a staff member identifier (e.g., an employee number) may be entered into the application program and associated via the user interface of the program so that monitored indicators are also associated with these identifiers.

[0104] The application program may support a site specific association between a monitoring device and a user terminal. In this way, device functionality can be geofenced so that any devices ‘out of range’ are disabled.Housing

[0105] Figure 4 of the drawings shows an embodiment of a monitoring device 400. In this exemplary embodiment the monitoring device 400 includes a sensor unit 410 that includes one or more medical sensors 412 (with associated electrode connectors 414). The sensor unit 410 may be housed in an internal housing 420 (being in the form of a case or container or box that can be flexible, rigid, or semi-rigid). The internal housing 420 may be placed in an external sensor housing 430, for example in the form of a flexible cradle, holder, pouch, sleeve, etc. The external housing 430 is configured to receive the sensor unit 410 (and the internal housing 420, if used), and the external housing 430 is adapted for application to the patient. The external sensor housing 430 is adapted to aid in the proper placement and spacing of the electrodes and / or sensors with respect to a person’s body.

[0106] In some embodiments, the external housing 430 includes an applicator 440 for securing the monitoring device to the patient’s body. For example, in one embodiment the applicator 440 may include a double sided sticker to secure the device onto a patient’s chest. The applicator 440 includes electrodes connected to conductive tracks (optionally including gel) to allow signal acquisition from the patient’s skin, and the electrodes 442 are positioned so that they are in conductive communication with the electrode connectors 414 of the sensors in the sensor unit 412. The signals acquired via the electrodes 442 are communicated to the electronic components of the sensor unit 412 via the conductors 442 (e.g., including the conductive tracks) associated with the external housing 430.

[0107] Additionally or alternatively other methods may be used to attach or hold the monitoring device 400 in place with respect to a patient, for example non-adhesive means may be used. In some embodiments the monitoring device 400 may be attached to or held secure with respect to a patient with the use of a harness or straps or the like.

[0108] In some embodiments, the 400 device has a unique identification number (UID) 416, and a user can find the UID 416 by either reading the number on the casing of the device, or by scanning a QR code, NFC code, or RFID code or the like that is provided on or at the internal and / or external housing of the device 400.

[0109] The monitoring device includes a controller 470 and a communications module 450 supporting one or more communication protocols (such as Bluetooth, WiFi, Wired USB-C, LoRA etc.) so that the vital signs and / or other measurements can be shared to a user terminal.

[0110] The monitoring device 400 includes a power supply 460, for example in the form of a battery. Due to associated risks to the patient within the medical device context, the device should not be charge or chargeable while in use. Accordingly, the power supply includes an isolation system to protect against any potential electrical risks to the patient.

[0111] The monitoring device battery 460 may be recharged by taking the internal housing 420 out of the external housing 430 (or in some embodiments via an access to the internal housing 420 and / or battery 460 through the external housing 430), and plugging the battery 460 in to a charging cable (e.g. a USB cable) via a charging socket 462. In various embodiments, the battery 460 may be fixed in the internal housing 420, or may be removable from the internal housing 420. In alternative embodiments the external housing 430 may include access to the charging socket 462. In some embodiments the power supply 460 may be wirelessly rechargeable.

[0112] Advantageously, the use of a USB interface allows for wired charging, transmission of data, and firmware / software updates. However, the power supply is configured to that plugging in the device does not automatically initiate charging, due to the associated electrical risks such as electrical shocks to the patient. The isolation system ensures that the device is chargeable via a USB connection, but that the device does not automatically charge when the device is downloading data via the USB (or any other) interface.

[0113] In some embodiments, the isolation circuit of the power supply is configured to disconnect the battery of the power supply from the device while the battery is charging. The battery may be charged via the USB interface from a connected electrical source (such as from a wall socket, a laptop, mobile device, etc.)

[0114] In some embodiments, the internal and / or external housing may include antimicrobial material. The allows for the device to be reusable on the same patient or on different patients when cleaned between use.

[0115] Figure 5 of the drawings shows an embodiment of a monitoring device 500 for medical measurements. The device 500 includes a sensor unit 510, with associated electronic componentry 511 housed within an internal housing 520, an external housing 530 (in the form of a cradle or cover) for housing and holding the sensor unit 510, and an adhesive applicator 540 (e.g., in the form of a sticker). The applicator 540 is configured to define the positions of the electrodes 542 and connect the sensor unit 510 and cradle assembly 532 onto a patient’s chest.

[0116] The cradle of the external housing 530 may be made of a flexible, moisture resistant, and soft material such as a polymer (e.g., silicone), suitable for multiple use (e.g., being “shower proof’, washable and durable). The external housing 530 may be in the form of various shapes and sizes suitable to hold the sensor unit 510 and to provide a contact surface 534 that contacts the patient’s skin (either directly or via an intermediate component, e.g. an applicator). The contact surface 534 may be flexible to conform to the patient’s body shape when the monitoring device is applied to the patient’s body.

[0117] In the illustrated embodiment, the sensor unit 510 is interposed between the cradle 530 and the sticker 540. The applicator 540 (e.g., in the form of a sticker) may be single use or multiple use (e.g., removably applicable, re-applicable, or movable). The applicator 540 comprises a flexible base layer supporting conducting tracks and electrodes 542. A plurality of conducting tracks are carried by the applicator, for example embedded within a base layer. A first side of the applicator is adapted to beconnectable to the device, for example comprising a first adhesive layer for adhering to the external housing. A second, opposite side of the applicator is adapted for placement on a patient, for example comprising a second adhesive layer for adhering to the patient’s skin. In some embodiments the first and second adhesive layers are different. In other embodiments the first and second adhesive layers may comprise the same or a similar type of adhesive.

[0118] The applicator 540 is adapted to match the external housing in shape and size thereby securely attaching the external housing to the patient. The applicator 540 is adapted so that the conducting tracks are in conductive communication with electrode points on the internal housing 520, thereby linking the internal electrode points to the external electrodes 542 on the applicator 540 that will be in contact with the patient’s skin.

[0119] In some embodiments the applicator comprises five electrode connection points for five electrodes (for example two ECG electrodes, two bioimpedance electrodes and one spare or backup electrode). In other embodiments, less or more electrodes may be provided on the applicator according to the application’s requirements.

[0120] Advantageously, the combination of the flexible external housing 530 and the specially adapted and configured applicator 540 allows for various shapes and sizes of the device 500. For example, the external housing and the applicator may have a size and shape so as to stretch between a patient’s shoulders across their chest, having a substantially oblong shape in order to position electrodes as required anywhere within the region covered by the device when applied to the patient from one shoulder to the other.

[0121] The monitoring device 500 may include at least one identifier, a Unique Identifier (UID), that a user is able to access e.g., in the form of an indicator on the casing 520, a QR code, a Near Field Communication (NFC) identifier, and / or via Bluetooth communication with a user terminal 130.

[0122] Figures 6A and 6B of the drawings show another embodiment of a monitoring device 600 for medical measurements. The device 600 includes a sensor unit 610, with associated electronic componentry 611 housed within an internal housing 620, an external housing 630 (with a contact surface 634) for housing and holding the sensor unit 610, and an adhesive applicator 640. The applicator 640 is configured to define the positions of the electrodes 642 and connect the sensor unit 610 and cradle assembly 632 onto a patient’s chest. The cradle of the external housing 630 may be made of a flexible, moisture resistant, and soft material such as a polymer (e.g., silicone), suitable for multiple use (e.g., being “shower proof’, washable and durable).Charge Connection

[0123] Figure 10 of the drawings shows a flow diagram of a charge disconnection method 1000. The method may be implemented by a controller (or a processor etc.) that forms part of a monitoring device as described herein. At 1010 a cable interface is polled to determine if a cable is connected.

[0124] If YES at 1020, then the monitoring device is operated in “wired mode” at 1022. If, at 1024, a command is received from a user terminal to enter wired mode (YES at 1026) then at 1028 wireless communication protocols are disabled, battery use is disabled, and battery charge is disabled. If, at 1024, no command is received (NO at 1030) then the controller determines at 1032 (e.g., based on an input signal from the device, from one or more sensors, and / or from a user interface, etc.) whether the device is applied to a patient, i.e., whether the device is in use. If YES, then charging is disabled at 1034. If NO, then charging is allowed and / or enabled at 1036. At 1040 the controller again ascertains whether the cable is connected or disconnected. In some embodiments, step 1040 and step 1010 may be the same step.

[0125] If, at step 1010, the controller determines that the cable is not connected then at 1050 the device is placed in a wireless mode. In some embodiments, wireless mode may be configured to be a default mode. At 1052 wireless communication technology is enabled (e.g. BLE, Wi-Fi, etc.), and at 1054 battery charging is enabled. Steps 1052 and 1054 may occur in series or in parallel. At 1060 the controller determines (e.g.,based on an input signal from the device, from one or more sensors, and / or from a user interface, etc.) whether the device is applied to a patient, i.e., whether the device is in use. If YES, then charging is disabled at 1064. If NO, then the controller again ascertains, at 1010, whether the cable is connected or disconnected.

[0126] In this way the isolation system of the power supply continuously monitors operation of the device and the power supply in order to connect and / or disconnect charging of the battery.Uses & Advantages

[0127] Unlike older cuffless approaches that rely only on optical PPG (sometimes with ECG), the method described herein adds a bioimpedance (BioZ) channel and treats it as the mechanical timing reference so the device can see the pre-ejection period (PEP) and separate it from the true pulse travel time. Concretely, the system samples ECG, PPG and BioZ at the same time, then computes pulse-arrival times from PPG and from BioZ and blends them in a simple linear model such as BP_Estimate = a-PAT(PPG) + b-PAT(BioZ) + c, which is explicitly disclosed, with PAT taken from each signal stream. The algorithm applied defines PAT as PTT + PEP, with PEP being measurable from features across the three biosignals (ECG for the electrical start, BioZ for aortic valve opening, and PPG for distal pulse), letting the algorithm capture and correct the PEP “mechanical delay” instead of ignoring or guessing it. In short, by deliberately combining optical and BioZ with ECG and using both PAT (PPG) and PAT(BioZ), the system turns PEP from a source of error into an input, enabling more reliable BP estimation using the integrated three-signal method.

[0128] Since vital signs are ubiquitous to healthcare, the monitoring devices and systems described herein can be used in all areas of healthcare e.g. personalised health, primary care, pre hospital care, hospital care, home care, telehealth, etc.

[0129] Applications for the monitoring systems described herein include, for example:a. Personalised health: Patients at home and unwell are able to measure their blood pressure, heart rhythm, oxygen level, temperature, or a combination of these. This provides objective medical diagnostic quality vital signs information. A carer of a patient (a parent with sick child, for example), may be alerted on their smart phone at night if the patient has a fever, their respiratory rate becomes abnormal, and / or their oxygen level becomes abnormal. The information again is of medical diagnostic quality and can also be shared with a treating healthcare professional. b. Primary care (e.g., GP): When a patient wears the patch for 72hrs (which has a greater accuracy than the prior art standard of measurement via cuff every 30 minutes for 24hrs) with frequent measurements e.g. every 10 minutes, the accurate diagnosis of hypertension is facilitated. The absence of a cuff means the patient is unaware when the measurements are taken, hence blood pressure is not elevated by the patient knowing it is being measured (known as ‘white coat hypertension’. Not previously possible, a patient can have their blood pressure, heart rate, and heart rhythm measured concurrently in real time outside a hospital setting, at home, and during their daily activities. Adding posture and activity information allows a more powerful analysis of what is actually happening when the patient has symptoms e.g. faint, fit, falls, dizzy on lying down, dizzy on standing up, dizzy in the shower, undiagnosed episodes of passing out, and monitoring of certain disease conditions e.g. Postural Orthostatic Tachycardia Syndrome (POTS). c. Prehospital care: With prior art methods it is difficult, if not impossible to obtain a full set of vital signs on patients in cars, ambulances, helicopters, aeroplanes, boats etc., due to movement artifact. The systems and methods described herein allows this to happen non- invasively, continuously, and wirelessly (or wired), in real time, and with the ability to share the information in real time to multiple healthcare providers. d. Hospital care: The monitoring device can be applied when the patient arrives at the hospital (or sooner if arriving by ambulance) and can stay on the patient throughout their hospitalisation without the need for multiple devices to measure a full set of vital signs, or connect! on / disconnecti on every time a vital sign is taken. The monitoring device allows for vital signs to be taken automatically, allowing for a decrease in manual nursing effort. By automating vital signs measurement, a deterioration score can be calculated automatically, with alerts to healthcare providers sent automatically. Adeterioration of patient status can be monitored in real time. Data analysis (e.g., via machine learning or other Al) facilitates an objective organisational approach prospectively and retrospectively to patient care and deterioration (e.g., detection of sepsis). A patient undergoing surgery can have vital signs measured in real time preoperatively (during assessment), intraoperatively (during operation) and post operatively in a continuum (not currently done) e. Home care: Vital signs measurement can be done on site or remotely by healthcare providers for conditions such as hospital in the home, home dialysis, home chemotherapy, post hospital care, and / or virtual hospital care. f. Telehealth: Rural and remote telehealth care provision is facilitated.

[0130] Advantageously, the systems, methods and devices described herein can be used to monitor a patient’s vital signs automatically and continuously. The information can easily be sent to the receiving device of one or more user terminals via wired and / or wireless connections. Blood pressure can be measured without a cuff on the arm, the device is rechargeable and reusable, and the overall lifetime cost is lower than existing methods because the monitoring device can be cleaned and reused (in embodiments including an applicator such as an adhesive, this component may need to be replaced).

[0131] Advantageously, recall of the vital signs can be instantaneous for a nurse beside the patient using a user terminal in communication with the patient’s monitoring device via a variety of communication protocols / methods.

[0132] Advantageously, the system and monitoring device may be used as a diagnostic regulated medical device (e.g., according to the class 2 standard).

[0133] Advantageously, the single monitoring device can measure a full set of vital signs when it includes multiple types of sensors. The monitoring device is light andsmall compared to other devices, is waterproof and can be worn in the shower, and is rechargeable and can be used many times.

[0134] Advantageously, real time location tracking may assist with patient flow, and / or with contact tracing should the patient (or another one in their proximity) be discovered to have an infectious disease.

[0135] Advantageously, the ‘cradle’ that forms the external housing can be in many shapes and designs to engage the user. The adhesion mechanism (e.g., a sticker) with the embedded electrodes can be made in a variety of sizes and shapes to accommodate the size of the patient, the accuracy of the measurements, or other new measurements that can be made.

[0136] Advantageously, the UID of the device can be ascertained very easily and rapidly. The monitoring device can be used wired or wirelessly.

[0137] From a functional viewpoint, the sensors, design, and electronics combined within the device allow the following: a. A rapid connection can be established between a patient’s monitoring device and the user terminal of a staff member, which is usually very tedious or manual in the prior art. b. Healthcare providers in a hospital are able to perform ‘hourly ward rounding’ using, e.g., wireless near-field communication technology which simplifies the process. c. Healthcare providers can retrieve vital signs data from the patient’s record in front of the patient very readily using near-field wireless communication (including staff that are authorised to do so, but are not usually caring for the patient e.g. in an emergency situation). d. Each vital sign parameter can be turned on or off, and the duration or interval between measurements can be changed. e. Measured parameters can be combined to derive a ‘deterioration score’ alert that can be transmitted to a user terminal or monitoring system.f. Measured parameters can be combined and processed (e.g. via machine learning or other artificial intelligence) to create ‘smart alarms’ for healthcare providers monitoring the patient, and / or to provide new insights e.g. the patient’s conscious state, degree of activity, seizures, etc.

[0138] It will be understood to persons skilled in the art of the invention that many modifications may be made without departing from the spirit and scope of the invention.

Claims

CLAIMS:

1. A physiological monitoring system comprising: a plurality of bio sensors; at least one processor coupled to the plurality of bio sensors, wherein the at least one processor is configured to: receive signals from the plurality of bio sensors; process the received signals to determine a photoplethysmography Pulse Arrival Time (PAT(PPG)) and a bioimpedance Pulse Arrival Time (PAT(BioZ)); and generate a blood-pressure estimate based on a combination of the determined PAT(PPG) and the determined PAT(BioZ) that compensates for pre-ejection period (PEP) variability.

2. The system of claim 1, wherein the plurality of bio sensors comprise: an electrocardiography (ECG) sensor; a bioimpedance (BioZ) sensor; and an optical photoplethysmography (PPG) sensor.

3. The system of claim 1 or claim 2, wherein the at least one processor is configured to estimate and continuously correct inter-channel delay and drift by updating per-channel offset parameters based on one or more of: cross-correlation between ECG and BioZ landmarks, similarity measures between landmark sequences, beat matching constrained by R-R intervals, and a calibration offset.

4. A method for estimating blood pressure, the method comprising: at a processor of a sensor system comprising a plurality of bio sensors: receiving signals from the plurality of bio sensors; processing the received signals to determine a photoplethysmography Pulse Arrival Time (PAT(PPG)) and a bioimpedance Pulse Arrival Time (PAT(BioZ)); and generating a blood-pressure estimate based on a combination of the determined PAT(PPG) and the determined PAT(BioZ) that compensates for preejection period (PEP) variability.

5. The method of claim 4, wherein receiving signals from the plurality of bio sensors comprises receiving: electrocardiography (ECG) signals, bioimpedance (BioZ) signals, andoptical photoplethysmography (PPG) signals.

6. The method of claim 4 or claim 5, comprising estimating and continuously correcting inter-channel delay and drift by updating per-channel offset parameters based on one or more of: cross-correlation between ECG and BioZ landmarks, similarity measures between landmark sequences, beat matching constrained by R-R intervals, and / or a calibration offset.

7. The method of any one of claims 4 to 6, comprising: determining a pre-ejection period (PEP) from an interval between an ECG fiducial and a BioZ mechanical fiducial.

8. The method of any one of claims 4 to 7, wherein receiving signals from the plurality of bio sensors comprises acquiring, in a time-aligned manner, ECG, BioZ and PPG signals from a subject.

9. The method of any one of claims 4 to 8, wherein processing the received signals to determine the PAT(PPG) and the PAT(BioZ) comprises: detecting an ECG fiducial corresponding to ventricular depolarization; detecting a BioZ fiducial corresponding to aortic valve opening; and detecting a PPG fiducial corresponding to a peripheral pulse landmark.

10. The method of any one of claims 4 to 9, wherein processing the received signals comprises: computing PAT(PPG) between an ECG fiducial and a PPG fiducial; and computing PAT(BioZ) between the ECG fiducial and a BioZ fiducial.

11. The method of any one of claims 4 to 10, wherein generating the blood-pressure estimate takes into consideration a pre-ejection period (PEP) that is a time interval between an ECG fiducial and a BioZ mechanical fiducial.

12. The method of any one of claims 4 to 11, wherein generating the blood pressure estimate comprises combining PAT(PPG) and PAT(BioZ) according to a parameterized model described by:BP Estimate = a *PA T (PPG) + b *PA T (BioZ) + c13. The method of claim 12, wherein coefficients a and b are obtained via an initial calibration step.

14. The method of any one of claims 4 to 13, wherein the blood pressure estimate is generated based on one or more of: age; height;BMI; a heart rate (HR); and a heart rate variability (HRV).

15. The method of any one of claims 4 to 14, wherein the method is used for cuffless blood-pressure estimation.

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