Are cuffless devices challenged enough? Design of a validation protocol for ambulatory blood pressure monitors at the wrist: the case of the Aktiia Bracelet.

The US and European guidelines for the diagnosis and management of hypertension recommend the introduction of systematic home and night Blood Pressure (BP) monitoring. Fully-automated wearable devices can address the needs of patients and clinicians by improving comfort while achieving measurement accuracy. Often located at the wrist and based on indirect BP measurements, these devices must address the challenges of ambulatory scenarios. New validation strategies are needed, but little guidance has been published so far.In this work, we propose an experimental protocol for the validation of cuffless wrist BP monitors that addresses ambulatory environment challenges in a controlled experimental setting. The protocol assesses the robustness of the measurement for different body postures, the ability of the device to track BP changes, and its ability to deal with hydrostatic pressure changes induced by different arm heights.Performance testing using Aktiia Bracelet is provided as an illustration. The results of this pilot study indicate that the Aktiia Bracelet can generate accurate BP estimates for sitting and lying positions and is not affected by hydrostatic pressure perturbations.Clinical Relevance- Automated cuffless BP monitoring is opening a new chapter in the way patients are being diagnosed and managed. This paper provides a guidance on how to assess the clinical utility of such devices when used in different body positions.

Cooperative dry-electrode sensors for multi-lead biopotential and bioimpedance monitoring.

Cooperative sensors is a novel measurement architecture that allows the acquiring of biopotential signals on patients in a comfortable and easy-to-integrate manner. The novel sensors are defined as cooperative in the sense that at least two of them work in concert to measure a target physiological signal, such as a multi-lead electrocardiogram or a thoracic bioimpedance.This paper starts by analysing the state-of-the-art methods to simultaneously measure biopotential and bioimpedance signals, and justifies why currently (1) passive electrodes require the use of shielded or double-shielded cables, and (2) active electrodes require the use of multi-wired cabled technologies, when aiming at high quality physiological measurements.In order to overcome the limitations of the state-of-the-art, a new method for biopotential and bioimpedance measurement using the cooperative sensor is then presented. The novel architecture allows the acquisition of the aforementioned biosignals without the need of shielded or multi-wire cables by splitting the electronics into separate electronic sensors comprising each of two electrodes, one for voltage measurement and one for current injection. The sensors are directly in contact with the skin and connected together by only one unshielded wire. This new configuration requires one power supply per sensor and all sensors need to be synchronized together to allow them to work in concert.After presenting the working principle of the cooperative sensor architecture, this paper reports first experimental results on the use of the technology when applied to measuring multi-lead ECG signals on patients. Measurements performed on a healthy patient demonstrate the feasibility of using this novel cooperative sensor architecture to measure biopotential signals and compliance with common mode rejection specification accordingly to international standard (IEC 60601-2-47) has also been assessed.By reducing the need of using complex wiring setups, and by eliminating the presence of central recording devices (cooperative sensors directly sense and store the measured biosignals on the site), the depicted novel technology is a candidate to a novel generation of highly-integrated, comfortable and reliable technologies that measure physiological signals in real-life scenarios.

Accurate walking and running speed estimation using wrist inertial data.

In this work, we present an accelerometry-based device for robust running speed estimation integrated into a watch-like device. The estimation is based on inertial data processing, which consists in applying a leg-and-arm dynamic motion model to 3D accelerometer signals. This motion model requires a calibration procedure that can be done either on a known distance or on a constant speed period. The protocol includes walking and running speeds between 1.8km/h and 19.8km/h. Preliminary results based on eleven subjects are characterized by unbiased estimations with 2(nd) and 3(rd) quartiles of the relative error dispersion in the interval ±5%. These results are comparable to accuracies obtained with classical foot pod devices.