Julien Penders

Julien Penders
Bloomlife

Master of Science

About

117
Publications
50,548
Reads
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3,485
Citations
Citations since 2017
17 Research Items
1906 Citations
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Introduction
Co-Founder of Bloomlife--a maternal health company combining connected devices with data analytics to increase access to care, provide personalized feedback to women, and help doctors earlier predict and manage pregnancy complications. Entrepreneur, engineer and scientist at the intersection of digital health and med tech. Research interests include digital health, wearable sensors, AI/ML for health, predictive analytics, consumer-centered health innovation, maternal and prenatal health.
Additional affiliations
January 2014 - June 2014
imec
Position
  • Project Manager
September 2006 - December 2013
Imec Netherlands
Position
  • Manager

Publications

Publications (117)
Article
This letter presents a 5-channel unipolar fetal electrocardiogram readout IC for monitoring the health of a fetus during pregnancy. Each readout channel includes an instrumentation amplifier, a programable gain amplifier and a successive approximation register ADC. A unipolar, common half branch reuse topology is used to achieve low noise, low powe...
Conference Paper
Full-text available
Preterm birth (PTB), or birth before the completion of 37 weeks of pregnancy, is the leading cause of neonatal morbidity and mortality and the second-leading cause of death in children under the age of five. The importance of early intervention to prevent and reduce the impact of PTB is clear. However, no solution is currently available to easily a...
Poster
Full-text available
Title* Early labour detection in laboratory and free-living conditions using combined electrohysterography and heart rate data Objective * Detection and management of complications such as preterm birth, could be improved by early labour detection. In our previous work, we showed that specific patterns in physiological data such as electrohysterogr...
Article
Detection and management of complications such as preterm birth, could be improved by early labour detection. In our previous work, we showed that specific patterns in physiological data such as electrohysterography (EHG) and heart rate (HR) could be used to build predictive statistical models able to detect labour. In this work we highlight how ph...
Poster
Full-text available
In this study, we present a hidden Markov model approach to pre-eclampsia (PE) diagnosis using the Viterbi algorithm. We aim at identifying PE in high-risk pregnancies monitored in hospital settings. The proposed model uses daily blood pressure measurements collected using commercially available sensors, starting at 20 weeks of gestational age. An...
Conference Paper
Full-text available
In this paper we show early evidence of the feasibility of detecting labour during pregnancy, non-invasively and in free-living. In particular, we present machine learning models aiming at dealing with the challenges of unsupervised, free-living data collection, such as identifying periods of high quality data and detecting physiological changes as...
Article
The IEEE International Conference on Biomedical and Health Informatics (BHI) is a special topic conference of the IEEE Engineering in Medicine and Biology Society (IEEEEMBS). BHI2017 was co-located with the annual HIMSS Conference & Exhibition in Rosen Plaza Hotel, Orlando, Florida, USA during Feb. 16-19, 2017. The focus of BHI2017 was on "informat...
Article
Full-text available
In this paper we propose a method combining electrohysterography (EHG) and heart rate (HR) data to detect labour. Labour detection may be helpful in providing just in time care and avoiding unnecessary antenatal visits. Given specific changes in physiological data such as EHG and HR highlighted from previous literature in correspondence of uterine...
Article
Full-text available
In this paper, we propose a method to improve accuracy of fetal kicks detection during pregnancy using a single wearable device placed on the abdomen. Monitoring fetal wellbeing is key in modern obstetrics as it is routinely used as a proxy to fetal movement. However, accurate, nonin-vasive, long-term monitoring of fetal movement is challenging, es...
Conference Paper
Monitoring fetal wellbeing is key in modern obstetrics. While fetal movement is routinely used as a proxy to fetal wellbeing, accurate, noninvasive, long-term monitoring of fetal movement is challenging. A few accelerometer-based systems have been developed in the past few years, to tackle common issues in ultrasound measurement and enable remote,...
Article
Full-text available
Monitoring fetal wellbeing is key in modern obstetrics. While fetal movement is routinely used as a proxy to fetal wellbeing, accurate, noninvasive, long-term monitoring of fetal movement is challenging. A few accelerometer-based systems have been developed in the past few years, to tackle common issues in ultrasound measurement and enable remote,...
Article
Full-text available
Altini M, Casale P, Penders J, ten Velde G, Plasqui G, Amft O. Cardiorespiratory fitness estimation using wearable sensors: Laboratory and free-living analysis of context-specific submaximal heart rates..—In this work, we propose to use pattern recognition methods to determine submaximal heart rate (HR) during specific contexts, such as walking at...
Article
Full-text available
Objective: In this paper we propose artificial intelligence methods to estimate cardiorespiratory fitness (CRF) in free-living using wearable sensor data. Methods: Our methods rely on a computational framework able to contextualize heart rate (HR) in free-living, and use context-specific HR as predictor of CRF without need for laboratory tests....
Article
Full-text available
In this work, we propose to use pattern recognition methods to determine submaximal heart rate (HR) during specific contexts, such as walking at a certain speed, using wearable sensors in free-living, and use context-specific HR to estimate cardiorespiratory fitness (CRF). CRF of 51 participants was assessed by a maximal exertion test (VO2max). Par...
Article
Full-text available
We introduce an approach to personalize energy expenditure (EE) estimates in free living. First we use Topic Models (TM) to discover activity composites from recognized activity primitives and stay regions in daily living data. Subsequently, we determine activity composites that are relevant to contextualize heart rate (HR). Activity composites wer...
Article
Accurate estimation of Energy Expenditure (EE) and cardiorespiratory fitness (CRF) is a key element in determining the causal relation between aspects of human behavior related to physical activity and health. In this paper we estimate CRF without requiring laboratory protocols and personalize energy expenditure (EE) estimation models that rely on...
Article
Full-text available
Maternal and infant health is a global healthcare problem affecting developing and developed countries alike. Pregnancy complications increase the risk of maternal and infant death, and are associated with adverse outcomes such as miscarriage, stillbirth, and preterm birth. Lifestyle modifications before and during pregnancy have been shown to redu...
Article
Full-text available
In this paper, we present a method to estimate oxygen uptake (VO2) during daily life activities and transitions between them. First, we automatically locate transitions between activities and periods of non-steady-state VO2. Subsequently, we propose and compare activity-specific linear functions to model steady-state activities and transition-speci...
Patent
Full-text available
An analog signal processor (ASP) application-specific integrated circuit (ASIC) is disclosed. The ACIS can be used for remotely monitoring ECG signals of a subject that has reduced power consumption. In one aspect, the ASIC performs the functions of: ECG signal extraction with high resolution using ECG readout channel, feature extraction using a ba...
Patent
Full-text available
Disclosed herein are methods and devices for monitoring a heartbeat. In one embodiment, the device may comprise a sensor package mountable over a pulse location of a user. The sensor package may include a first sensor element configured to sense at least one signal at the pulse location and to provide a first output signal comprising a heart pulse...
Article
Full-text available
Introduction: This article is part of the focus theme of Methods of Information in Medicine on "Pervasive Intelligent Technologies for Health". Background: Energy Expenditure (EE) estimation algorithms using Heart Rate (HR) or a combination of accelerometer and HR data suffer from large error due to inter-person differences in the relation betwe...
Article
Full-text available
In this paper we propose a generic approach to reduce inter-individual variability of different physiological signals (HR, GSR and respiration) by automatically estimating normalization parameters (e.g. baseline and range). The proposed normalization procedure does not require a dedicated personal calibration during system setup. On the other hand,...
Article
Monitoring human brain activity has great potential in helping us understand the functioning of our brain, as well as in preventing mental disorders and cognitive decline and improve our quality of life. Non-invasive surface EEG is the dominant modality for studying brain dynamics and performance in real-life interaction of humans with their enviro...
Article
Full-text available
Several methods to estimate Energy Expenditure (EE) using body-worn sensors exist, however quantifications of the differences in estimation error are missing. In this paper, we compare three prevalent EE estimation methods and five body locations to provide a basis for selecting among methods, sensors number and positioning. We considered (a) count...
Conference Paper
Full-text available
Accurate Energy Expenditure (EE) estimation is key in understanding how behavior and daily Physical Activity (PA) patterns affect health. Mobile phones and wearable sensors (e.g. accelerometers (ACC) and heart rate (HR) monitors) have been widely used to monitor PA. In this paper we present a real-time implementation of activity-specific EE estimat...
Conference Paper
Full-text available
Physical Activity (PA) is one of the most important determinants of health. Wearable sensors have great potential for accurate assessment of PA (activity type and Energy Expenditure (EE)) in daily life. In this paper we investigate the benefit of multiple physiological signals (Heart Rate (HR), respiration rate, Galvanic Skin Response (GSR), skin h...
Conference Paper
A low power and convenient bio-impedance monitor, which relies on a proprietary ASIC to achieve low power performance, is shown. It can be used in several bio-impedance applications, especially in continuous and wearable applications thanks to its compact form factor and long battery life time. In this paper, we demonstrate its performance for resp...
Conference Paper
Dry electrodes provide the possibility of moving EEG usage from the research and clinical environment to real life applications. Having a framework for evaluating the performance of dry electrodes would facilitate this process and help EEG system developers to test their designs. This paper describes an evaluation method for dry electrode EEG recor...
Conference Paper
Full-text available
Ambulatory mental stress monitoring requires long-term physiological measurements. This paper presents a data collection protocol for ambulatory recording of physiological parameters for stress measurement purposes. We present a wearable sensor system for ambulatory recording of ECG, EMG, respiration and skin conductance. The system also records va...
Conference Paper
Timely mental stress detection can help to prevent stress-related health problems. The aim of this study was to identify those physiological signals and features suitable for detecting mental stress in office-like situations. Electrocardiogram (ECG), respiration, skin conductance and surface electromyogram (sEMG) of the upper trapezius muscle were...
Article
Full-text available
Electroencephalography (EEG) testing in clinical labs makes use of large amplifiers and complex software for data acquisition. While there are new ambulatory electroencephalogram (EEG) systems, few have been directly compared to a gold standard system. Here, an ultra-low power wireless EEG system designed by Imec is tested against the gold standard...
Conference Paper
The success of applying dry sensor technology in measuring electroencephalogram (EEG) signals will have a significant impact on a wider adoption of brain activity monitoring in ambulatory as well as real life solutions. The presence of motion artifacts is the major obstacle in applying dry sensors for long-term EEG monitoring. In this paper we asse...
Article
Full-text available
Wearable sensors have great potential for accurate estimation of Energy Expenditure (EE) in daily life. Advances in wearable technology (miniaturization, lower costs), and machine learning techniques as well as recently developed self-monitoring movements, such as the Quantified Self, are facilitating mass adoption. However, EE estimations are affe...
Conference Paper
Full-text available
Body sensor networks (BSNs) have provided the opportunity to monitor energy expenditure (EE) in daily life and with that information help reduce sedentary behavior and ultimately improve human health. Current approaches for EE estimation using BSNs require tedious annotation of activity types and multiple body sensor nodes during data collection an...
Article
Full-text available
In this paper, we present a new bio-impedance monitor for wearable and continuous monitoring applications. The system consumes less than 14.4mW when measuring impedance, and 0.9mW when idling. Its compact size (4.8cm × 3cm × 2cm) makes it suitable for portable and wearable use. The proposed system has an accuracy of 0.5Ω and resolution of 0.2Ω on b...
Conference Paper
Full-text available
Accurate Energy Expenditure (EE) estimation is key in understanding how behavior and daily physical activity (PA) patterns affect health, especially in today's sedentary society. Wearable accelerometers (ACC) and heart rate (HR) sensors have been widely used to monitor physical activity and estimate EE. However, current EE estimation algorithms hav...
Conference Paper
The cost of healthcare is increasing worldwide. Without disruptive changes, a large part of the population in many developed countries will no longer be able to afford healthcare by 2040. Part of the solution will come from focusing on prevention. Having personal tools at everyone's disposal, which will help people to monitor their health and to ch...
Article
Full-text available
Ambulatory monitoring of the electrocardiogram (ECG) is a highly relevant topic in personal healthcare. A key technical challenge is overcoming artifacts from motion in order to produce ECG signals capable of being used in clinical diagnosis by a cardiologist. An electrode-tissue impedance is a signal of significant interest in reducing the motion...
Conference Paper
Full-text available
In this paper, we present a miniaturized (<6cm(3)) and low noise (60nV/root Hz) wireless EEG sensor node with active electrodes and simultaneous electrode tissue impedance (ETI) monitoring. The added benefit of the active electrodes and continuous ETI monitoring is quantified in terms of susceptibility against power line interference and cable moti...
Conference Paper
Full-text available
A motion artifact removal method with a two-stage cascade LMS adaptive filter is proposed for an ambulatory ECG monitoring system. The first LMS stage consisting of analog feedback prevents the signal saturation to reduce the input dynamic range. An adaptive step-size LMS algorithm is introduced and employed for the second LMS stage. The adaptive s...
Conference Paper
Full-text available
Accurate estimation of Energy Expenditure (EE) in ambulatory settings is a key element in determining the causal relation between aspects of human behavior related to physical activity and health. We present a new methodology for activity-specific EE algorithms. The proposed methodology models activity clusters using specific parameters that captur...
Conference Paper
It is well known that chronic mental stress can cause health problems. Early stress detection can help prevent these problems. We propose and compare two approaches to estimate stress level from physiology. We have measured physiological signals in three different artificial stressful conditions involving problem solving under time pressure and mem...
Article
Full-text available
Heart rhythm and respiration rate are two vital signs that are of interest for ambulatory monitoring. However, noise due to activity in ambulatory monitoring complicates the ECG interpretation. This paper describes a set of algorithms to robustly monitor a subject's heart rhythm and respiration rate in an ambulatory environment. To ensure robustnes...
Conference Paper
Full-text available
Recent advances in low-power micro-electronics are revolutionizing ECG monitoring. Wearable patches now allow comfortable monitoring over several days. Achieving reliable and high integrity recording however remains a challenge, especially under daily-life activities. In this paper we present a system approach to motion artifact reduction in ambula...
Conference Paper
Full-text available
This paper presents the development of an ECG patch aiming at long term patient monitoring. The use of the recently standardized Bluetooth Low Energy (BLE) technology, together with a customized ultra-low-power ECG System on Chip (ECG SoC). including Digital Signal Processing (DSP) capabilities, enables the design of ultra low power systems able to...
Chapter
Many national health services struggle in the face of financial resource constraints and shortages of skilled labor. The cost of healthcare delivery is steadily on an upward trend. US health care spending is estimated at approximately 16% of the GDP [1]. This upward trend is expected to continue, with projections that the healthcare share of the GD...
Article
Vagus nerve stimulation (VNS) is a therapeutic option for individuals with refractory epilepsy. Individuals with refractory epilepsy are prone to dysfunction of the autonomic nervous system. Reduced heart rate variability is a marker of dysfunction of the autonomic nervous system. Our goal was to study heart rate variability in children with refrac...
Conference Paper
Full-text available
The cost of health care in first-world countries is increasing dramatically as a result of advances in medicine, a population that is becoming older and an increasingly unhealthy lifestyle. Personal health care concepts where sensors within and around the body monitor and measure all kind of physiological signals can be an addition to medicare with...
Article
DEEP brain stimulation implants have improved life quality for more than 70,000 patients world-wide with diseases like Parkinson's, essential tremor, or obsessive-compulsive disorder where pharmaceutical therapies alone could not offer sufficient relief. Still, optimization and monitoring relies heavily on regular clinical visits, putting a burden...
Article
Early mental stress detection can prevent many stress related health problems. This study aimed at using a wearable sensor system to measure physiological signals and detect mental stress. Three different stress conditions were presented to a healthy subject group. During the procedure, ECG, respiration, skin conductance, and EMG of the trapezius m...
Article
Monitoring patients' physiological signals during their daily activities in the home environment is one of the challenge of the health care. New ultra-low-power wireless technologies could help to achieve this goal. In this paper we present a low-power, multi-modal, wearable sensor platform for the simultaneous recording of activity and physiologic...
Article
Full-text available
The design and fabrication of a novel 2-scale topography dry electrode using macro and micro needles is presented. The macro needles enable biopotential measurements on hairy skin, the function of the micro needles is to decrease the electrode impedance even further by penetrating the outer skin layer. Also, a fast and reliable impedance characteri...
Article
Intelligent affective computers can have many medical and non-medical applications. However today's affective computers are limited in scope by their transferability to other application environments or that they monitor only one aspect of physiological emotion expression. Here, the use of a wireless EEG system, which can be implemented in a body a...
Article
Full-text available
Fall prevention in elderly subjects is often based on training and rehabilitation programs that include mostly traditional balance and strength exercises. By applying such conventional interventions to improve gait performance and decrease fall risk, some important factors are neglected such as the dynamics of the gait and the motor learning proces...
Conference Paper
This paper describes a mixed-signal ECG System-on-chip (SoC) that is capable of implementing configurable functionality with low-power consumption for portable ECG monitoring applications. A low-voltage and high performance analog front-end extracts 3-channel ECG signals and single channel impedance measurement with high signal quality. A custom di...
Conference Paper
Full-text available
Miniaturized, low power and low noise circuits and systems are instrumental in bringing EEG monitoring to the home environment. In this paper, we present a miniaturized, low noise and low-power EEG wireless platform integrated into a wearable headset. The wireless EEG headset achieves remote and wearable monitoring of up to 8 EEG channels. The head...
Article
form only given. Recent advances in micro-electronics and sensors open new perspectives in healthcare and lifestyle. New sensors and read-out circuits make recording of physiological signals accessible outside the hospital, and more comfortable than ever. Advanced signal processing algorithms and circuits allow monitoring of patients on-the-move. U...
Article
Full-text available
In order for wireless body area networks to meet widespread adoption, a number of security implications must be explored to promote and maintain fundamental medical ethical principles and social expectations. As a result, integration of security functionality to sensor nodes is required. Integrating security functionality to a wireless sensor node...
Conference Paper
A wireless ECG monitoring system is presented that is able to perform high-quality ECG signal acquisition, beat detection, and real time monitoring of skin-electrode impedance which can be used to monitor the presence of motion artefacts. The whole system consumes only 170μW while performing local beat detection. The beat detection algorithm was ve...
Article
This study describes the validation of a new wearable system for assessment of 3D spatial parameters of gait. The new method is based on the detection of temporal parameters, coupled to optimized fusion and de-drifted integration of inertial signals. Composed of two wirelesses inertial modules attached on feet, the system provides stride length, st...