Wearable Technologies for Healthcare Innovation

Healthcare is becoming more and more prone to technology. For this reason products are being developed geared toward implementing more sufficient ways of providing healthcare. Wearable technology has become one of the leading and considerably most valuable assets within the category. There are many types of wearable technology that do various tasks concerning health. Whether intended focus is on filling a void where human-error can be present or creation of a process where one was obsolete, wearable technology’s presence is felt within healthcare today. This exploratory study reviews wearable technologies that exist, are being used, as well as those that are developing or in the ideation phase concerning healthcare. We present a summary of wearable technologies used in healthcare and sample categorization to serve as a working framework for understanding the future direction of the field. Exemplar cases are provided

Evaluating devices for the measurement of auditory-evoked fetal movement

Determining normal and abnormal fetal function in utero in order to better predict which fetuses are at risk for adverse outcome is critical. However, the medical imaging tools that could assist with diagnosis are very expensive and rarely available in the developing world. In this study, we developed a prototype audio-motio-tachograph (AMTG), which measures fetal movements through the recording of abdominal wall deformations and tested it in Rwanda. First, we showed that AMTG detected fetal signals and that fetuses respond to complex acoustic stimuli. In order to improve the sensitivity of the device, we then measured whole abdominal wall deformations in an automated way using a lab-based 3D optical measurement system, in which fringes are projected and the deflections recorded with a camera. We found that abdominal wall deformations can be measured accurately with a non-invasive measurement apparatus. Overall, we conclude that wearable modalities provide a promising alternative assessment capacity in fetal research, especially in low income countries

Developing customized NIRS-EEG for infant sleep research: methodological considerations

Significance: Studies using simultaneous functional near-infrared spectroscopy (fNIRS)-electroencephalography (EEG) during natural sleep in infancy are rare. Developments for combined fNIRS-EEG for sleep research that ensure optimal comfort as well as good coupling and data quality are needed. // Aim: We describe the steps toward developing a comfortable, wearable NIRS-EEG headgear adapted specifically for sleeping infants ages 5 to 9 months and present the experimental procedures and data quality to conduct infant sleep research using combined fNIRS-EEG. // Approach: N = 49 5- to 9-month-old infants participated. In phase 1, N = 26 (10 = slept) participated using the non-wearable version of the NIRS-EEG headgear with 13-channel-wearable EEG and 39-channel fiber-based NIRS. In phase 2, N = 23 infants (21 = slept) participated with the wireless version of the headgear with 20-channel-wearable EEG and 47-channel wearable NIRS. We used QT-NIRS to assess the NIRS data quality based on the good time window percentage, included channels, nap duration, and valid EEG percentage. // Results: The infant nap rate during phase 1 was ∼40 % (45% valid EEG data) and increased to 90% during phase 2 (100% valid EEG data). Infants slept significantly longer with the wearable system than the non-wearable system. However, there were more included good channels based on QT-NIRS in study phase 1 (61%) than phase 2 (50%), though this difference was not statistically significant. // Conclusions: We demonstrated the usability of an integrated NIRS-EEG headgear during natural infant sleep with both non-wearable and wearable NIRS systems. The wearable NIRS-EEG headgear represents a good compromise between data quality, opportunities of applications (home visits and toddlers), and experiment success (infants’ comfort, longer sleep duration, and opportunities for caregiver–child interaction)

BIOTEX-biosensing textiles for personalised healthcare management.

Textile-based sensors offer an unobtrusive method of continually monitoring physiological parameters during daily activities. Chemical analysis of body fluids, noninvasively, is a novel and exciting area of personalized wearable healthcare systems. BIOTEX was an EU-funded project that aimed to develop textile sensors to measure physiological parameters and the chemical composition of body fluids, with a particular interest in sweat. A wearable sensing system has been developed that integrates a textile-based fluid handling system for sample collection and transport with a number of sensors including sodium, conductivity, and pH sensors. Sensors for sweat rate, ECG, respiration, and blood oxygenation were also developed. For the first time, it has been possible to monitor a number of physiological parameters together with sweat composition in real time. This has been carried out via a network of wearable sensors distributed around the body of a subject user. This has huge implications for the field of sports and human performance and opens a whole new field of research in the clinical setting

Automatic Detection of Epileptic Seizures in Neonatal Intensive Care Units through EEG, ECG and Video Recordings: A Survey

In Neonatal Intensive Care Units (NICUs), the early detection of neonatal seizures is of utmost importance for a timely, effective and efficient clinical intervention. The continuous video electroencephalogram (v-EEG) is the gold standard for monitoring neonatal seizures, but it requires specialized equipment and expert staff available 24/24h. The purpose of this study is to present an overview of the main Neonatal Seizure Detection (NSD) systems developed during the last ten years that implement Artificial Intelligence techniques to detect and report the temporal occurrence of neonatal seizures. Expert systems based on the analysis of EEG, ECG and video recordings are investigated, and their usefulness as support tools for the medical staff in detecting and diagnosing neonatal seizures in NICUs is evaluated. EEG-based NSD systems show better performance than systems based on other signals. Recently ECG analysis, particularly the related HRV analysis, seems to be a promising marker of brain damage. Moreover, video analysis could be helpful to identify inconspicuous but pathological movements. This study highlights possible future developments of the NSD systems: a multimodal approach that exploits and combines the results of the EEG, ECG and video approaches and a system able to automatically characterize etiologies might provide additional support to clinicians in seizures diagnosis

Antepartum Fetal Monitoring through a Wearable System and a Mobile Application

Prenatal monitoring of Fetal Heart Rate (FHR) is crucial for the prevention of fetal pathologies and unfavorable deliveries. However, the most commonly used Cardiotocographic exam can be performed only in hospital-like structures and requires the supervision of expert personnel. For this reason, a wearable system able to continuously monitor FHR would be a noticeable step towards a personalized and remote pregnancy care. Thanks to textile electrodes, miniaturized electronics, and smart devices like smartphones and tablets, we developed a wearable integrated system for everyday fetal monitoring during the last weeks of pregnancy. Pregnant women at home can use it without the need for any external support by clinicians. The transmission of FHR to a specialized medical center allows its remote analysis, exploiting advanced algorithms running on high-performance hardware able to obtain the best classification of the fetal condition. The system has been tested on a limited set of pregnant women whose fetal electrocardiogram recordings were acquired and classified, yielding an overall score for both accuracy and sensitivity over 90%. This novel approach can open a new perspective on the continuous monitoring of fetus development by enhancing the performance of regular examinations, making treatments really personalized, and reducing hospitalization or ambulatory visits. Keywords: tele-monitoring; wearable devices; fetal heart rate; telemedicin

Machine Learning and IoT Applied to Cardiovascular Diseases Identification through Heart Sounds: A Literature Review

N/

A Model for patient engagement integration in perinatal eHealth development and quality assurance

The aim of this study was to construct a model for patient engagement integration in perinatal eHealth development and quality assurance. The model was developed in four phases. The first three phases produced evidence for the development of a model. In the final phase, a qualitative interpretive synthesis was conducted using grounded theory to articulate a patient engagement model composed of three steps. The first phase was a scoping review aimed at describing the nature and range of patient engagement from the perspective of access, personalization, commitment, and therapeutic alliance within perinatal eHealth. A narrative synthesis was used to describe findings. Phase two consisted of two studies exploring engagement practices of pregnant users during their use of a self-monitoring health promotion eHealth system. A descriptive comparative analysis was completed to understand user engagement patterns based on physical use of the wearable device. A mixed-methods convergence evaluation was conducted to understand the process of accessing the health promotion eHealth system. In phase three a process evaluation tool for parent participation and collaboration (in the neonatal intensive care unit) was developed and psychometrically tested. For the interpretive synthesis, articles from the first three phases of this study were purposively sampled. A deductive codebook was developed using Donabedian’s model, and an adapted version of Lewin’s Action Research Cycle. Donabedian’s model consists of quality assurance through the examination of structure, process, and outcomes. Lewin’s Action Research Cycle informs iterative steps in development and implementation of health systems. Phase four resulted in a model for patient engagement integration in perinatal eHealth development and quality assurance. Three steps of the model were identified as being: Person-centered Perinatal eHealth program mapping; Process evaluation through monitoring of patient engagement processes; and Co-creation of perinatal eHealth programs through real-life testing of perinatal eHealth systems.Malli potilaan osallistumisesta perinataaliajan sähköisen terveydenhuollon kehittämiseen ja laadunvarmistukseen Tutkimuksen tavoitteena oli kehittää malli ohjaamaan potilaan osallistumista perinataaliajan sähköisen terveydenhuollon kehittämiseen ja laadunvarmistukseen. Malli kehitettiin neljässä vaiheessa. Kolmessa ensimmäisessä vaiheessa tuotettiin tutkimusnäyttöä kehittämisen tueksi. Viimeisessä vaiheessa laadullisen tulkitsevan synteesin avulla muodostettiin potilaan sitoutumisen malli. Ensimmäisessä vaiheessa tehtiin kartoittava kirjallisuuskatsaus, joka kuvasi potilaiden sähköiseen terveydenhuoltoon osallistumisen tavat ja laajuuden saatavuuden, yksilöllisyyden, sitoutumisen ja terapeuttisen hoitosuhteen näkökulmasta. Aineisto analysoitiin teorialähtöisellä sisällönanalyysillä ja tulokset kuvattiin narratiivisen synteesin avulla. Toinen vaihe muodostui kahdesta tutkimuksesta, jotka tarkastelivat itsemonitorointisysteemin avulla raskaana olevien henkilöiden osallistumistapoja terveydenedistämiseen. Tutkimuksissa odottajat käyttivät itsemonitorointisysteemiä. Osallistumistapoja analysoitiin puettavan laitteen käyttöajan pohjalta tehtyjen vertailevien analyysien avulla. Monimenetelmällisessä tutkimuksessa muodostettiin analyysin pohjalta ymmärrys itsemonitorointisysteemin saatavuuteen liittyvästä prosessista. Kolmannessa vaiheessa kehitettiin ja psykometrisesti testattiin prosessievaluaatiomittari arvioimaan vanhempien osallistumista ja yhteistyötä henkilökunnan kanssa vastasyntyneiden teho-osastolla. Viimeisen vaiheen tulkitsevaa synteesiä varten valittiin tarkoituksenmukaisia artikkeleita. Donabedianin terveydenhuollon laadunvarmistuksen malli ja Lewinin muokatun toimintatutkimuksen syklin pohjalta muodostettiin teorialähtöinen analyysirunko. Neljännen vaiheen tuloksena muodostettiin malli potilaan osallistumisesta perinataaliajan sähköisen terveydenhuollon kehittämiseen ja laadunvarmistukseen. Malli kostuu kolmesta askeleesta: Yksilökeskeisen sähköisen terveydenhuollon kartoitus, potilaan osallistumisprosessin monitorointiin perustuva prosessievaluaatio ja perinataaliajan sähköisen terveydenhuollon yhteiskehittäminen kliinisessä todellisuudessa