Measuring the effects of cognitive stress and relaxation using a wearable smart ring

Abstract. Prolonged stress is known to be a risk factor for various kinds of diseases, such as cardiovascular diseases. If stress could be easily measured, it would enable monitoring of stress and help people make better choices to achieve a healthier lifestyle. In this study, a polysomnography system as well as a wearable smart ring were used to measure the responses of central and autonomic nervous systems from ten healthy test subjects (five male and five female), aged 23–26. The responses were measured in two conditions: cognitive stress induced by a mental calculation task and relaxation induced by a focused attention meditation exercise. Power spectral densities of two electroencephalography frequency bands, alpha and beta, were calculated to represent the central nervous system response. The autonomic nervous system response was measured using heart rate, heart rate variability and peripheral (finger) temperature. In cognitive stress, alpha and beta bands both showed higher activity, increasing by 53.26% and 94.70%, respectively. Heart rate also increased by 19.33%, while heart rate variability decreased by 25.65% and peripheral temperature change was 0.77℃ lower. Results show that the changes in autonomic nervous system responses acquired by the smart ring correlate with the changes in central nervous system responses acquired by the polysomnography system. This suggests that a smart ring could be used for an indirect measurement of human stress level. Follow-up studies with larger sample sizes are needed to confirm the findings of this study and to determine the most suitable features for representation of human stress level.Kognitiivisen stressin ja rentoutumisen vaikutusten mittaaminen älysormuksella. Tiivistelmä. Pitkittynyt stressi toimii riskitekijänä lukuisille sairauksille, kuten sydän- ja verisuonitaudeille. Stressin vaivaton mittaaminen mahdollistaisi stressitason seuraamisen, mikä vuorostaan auttaisi ihmisiä tekemään parempia valintoja terveellisemmän elämäntyylin puolesta. Tässä tutkimuksessa käytettiin polysomnografialaitteistoa sekä puettavaa älysormusta keskushermoston ja autonomisen hermoston vasteiden mittaamiseen kymmeneltä terveeltä koehenkilöltä (viisi miestä ja viisi naista), iältään 23–26. Vasteet mitattiin kahdessa tilassa: päässälaskutehtävän aikaansaamassa kognitiivisessa stressissä sekä hengitykseen keskittyvän meditaatioharjoituksen aikaansaamassa rentoutumisessa. Kahdelle elektroenkefalografian taajuuskaistalle, alfalle ja beetalle, laskettiin tehon spektritiheydet kuvastamaan keskushermoston vastetta. Lisäksi laskettiin syke, sykevälivaihtelu sekä ääreislämpötila (sormen lämpötila) kuvastamaan autonomisen hermoston vastetta. Kognitiivisessa stressissä sekä alfa- että beetakaistan aktiivisuus kasvoi, alfalla 53,26 % ja beetalla 94,70 %. Myös syke nousi 19,33 %, kun taas sykevälivaihtelu pieneni 25,65 % ja ääreislämpötilan muutos oli 0,77 ℃ pienempi. Tulokset osoittavat, että älysormuksella mitatut autonomisen hermoston vasteen muutokset korreloivat polysomnografialaitteistolla mitattujen keskushermoston vasteen muutosten kanssa. Tämä antaa ymmärtää, että älysormusta voitaisiin käyttää ihmisen stressitason epäsuoraan mittaamiseen. Suuremman kokoluokan jatkotutkimuksia tarvitaan varmistamaan tämän tutkimuksen löydökset sekä määrittämään sopivimmat fysiologiset piirteet kuvastamaan ihmisen stressitasoa

Wearable Blood Pressure Device For Detection of Orthostatic Hypotension

Orthostatic hypotension may be described as an inevitable response from the body in the form of a drop in blood pressure after changing positions. This quick drop in blood pressure can cause a syncopal episode, often injuring victims. There are limitations in the currently used cuff-type blood pressure sensor, which is used in healthcare settings, in that it does not continuously measure blood pressure. This research project developed a wearable device that measures heart rate variability (HRV) to detect changes in blood pressure using the correlation between the two measurements. The instrumentation was developed and included a commercially available pulse oximetry sensor (MAX30101, Maxim Integrated, CA), which collected data used to calculate heart rate and HRV. A study was conducted as a series of head-tilt table tests to monitor changes in blood pressure and correlate this with HRV

Quantification of Physical Activity and Sleep Behaviors with Wearable Sensors : Analysis of a large-scale real-world heart rate variability dataset

Puettavia mittalaitteita, kuten älykelloja, voidaan käyttää arjessa oman terveydentilan, fyysisen kunnon, terveyskäyttäytymisen sekä hyvinvoinnin seuraamiseen. Puettavien mittalaitteiden käyttö on nykyisin suosittua, ja kuluttajat mittaavat niillä yleensä liikuntaa ja unta. Puettavien mittalaitteiden keräämä mittausaineisto on esimerkki arkielämän aineistoista (real-world data), jotka voivat tarjota käytännönläheisiä havaintoja terveydestä ja hyvinvoinnista. Arkielämässä kerättyjen aineistojen hyödyntäminen tutkimustarkoituksiin on kuitenkin haastavaa, sillä kuluttajat käyttävät puettavia mittalaitteita vapaaehtoisesti arkielämän olosuhteissa. Siksi aineiston käsittelyssä on otettava huomioon aineiston keräyksen kontrolloimattomat tutkimusasetelmien ulkopuoliset olosuhteet, jotka aiheuttavat mittausaineistoon tyypillisesti epätarkkuutta ja puutteellisuutta sekä otospopulaation valikoituneisuutta. Puettavien mittalaitteiden tuottamille jatkuva-aikaisille aineistoille ei myöskään toistaiseksi ole vakiintuneita käsittelytapoja. Näiden tekijöiden vuoksi puettavien mittalaitteiden keräämiä aineistoja käytetään nykyisin vielä vain vähän tutkimuksissa, vaikka ne voivat tarjota uusia havaintoja terveyskäyttäytymisestä ja hyvinvoinnista. Väitöstyössä hyödynnetään puettavan sydämen sykevälivaihtelua mittaavan laitteen tuottamaa arkielämän suurta aineistoa määrittämään liikuntaan ja uneen liittyvää käyttäytymistä. Liikunta ja uni ovat tärkeitä terveyskäyttäytymisen tekijöitä, ja väitöstyössä tutkitaan erityisesti liikunnan määrittämisen menetelmiä, liikuntakäyttäytymisen ajallista vaihtelua, sekä liikunnan, alkoholin nauttimisen ja muiden elämäntapojen vaikutusta uneen. Lisäksi väitöstyön tavoitteena on arvioida puettavien mittalaitteiden tuottamien suurten arkielämän aineistojen ja niiden hyödyntämisen soveltuvuutta tieteellisen tutkimukseen sekä osoittaa näiden aineistojen tarjoamia uusia havaintoja ja näkökulmia terveydestä ja hyvinvoinnista. Väitöstutkimuksen aineistona käytettiin 52 273 suomalaisen työntekijän tunnisteettomia arkielämässä tehtyjä sydämen sykevälivaihtelun mittauksia, jotka oli alun perin tehty osana terveyttä edistävää ja ennaltaehkäisevää terveydenhuoltoa. Aineisto on kerätty Firstbeat Technologies Oy:n toimesta, joka kehittää ja tarjoaa sykevälivaihtelun analyysimenetelmiä liikunnan, stressin ja palautumisen arviointiin. Aineisto sisälsi kolmipäiväisiä jatkuva-aikaisia mittauksia sydämen sykevälivaihtelusta sekä itseraportointeja nautitusta alkoholin määrästä sekä työ- että nukkumisajoista. Väitöstyössä liikunnan määrittämisessä hyödynnettiin sykevälivaihteluun perustuvaa hapenoton arviota. Unta arvioitiin autonomisen hermoston säätelyn kautta käyttäen perinteisiä sykevälivaihtelumuuttujia sekä uudenlaisia sykevälivaihteluun perustuvia palautumismuuttujia. Väitöstyön tulokset pohjautuvat sekä perinteisiin tilastollisiin että koneoppimisen menetelmiin. Liikuntakäyttäytymisessä havaittiin ajallista vaihtelua: liikunnan määrä oli korkein viikonloppuisin sekä alkuvuonna. Kun liikuntaa arvioitiin absoluuttisella hapenotolla, liikunnan määrä oli korkeampi miehillä kuin naisilla, ja nuoremmilla kuin vanhemmilla sekä normaalipainoisilla kuin lihavilla henkilöillä. Toisaalta kun liikunnan määrää arvioitiin ottaen huomioon henkilöiden kuntotaso, erot liikunnan määrässä henkilöiden välillä pieneni huomattavasti. Lisäksi liikuntakäyttäytymisellä havaittiin olevan yhteys uneen. Päivällä harrastettu liikunta näytti heikentävän autonomisen hermoston parasympaattista säätelyä unen aikana, mutta säännöllinen liikunta näytti lisäävän parasympaattista säätelyä ja palautumista unen aikana. Unen aikaisen autonomisen hermoston säätelyn kannalta tärkein tekijä oli kuitenkin päivän aikana nautittu alkoholi. Jo 1–2 alkoholiannosta heikensi autonomisen hermoston parasympaattista säätelyä unen aikana ja tämä säätely heikkeni sitä enemmän, mitä useampia alkoholiannoksia päivän aikana nautittiin. Painoon suhteutettu, sama alkoholimäärä näytti vaikuttavan autonomisen hermoston säätelyyn enemmän nuoremmilla kuin vanhemmilla henkilöillä, mutta samalla tavalla sekä paljon että vähän liikuntaa harrastavilla henkilöillä, ja sekä miehillä että naisilla. Monet väitöstyön tulokset tukevat aiempia tutkimustuloksia, kuten esimerkiksi havainnot suuremmasta liikunta-aktiivisuudesta viikonloppuisin, miesten, nuorten ja normaalipainoisten suuremmasta liikuntamäärästä absoluuttisella hapenottomäärällä mitattuna, sekä liikunnan ja alkoholin yhteydestä autonomisen hermoston säätelyyn unen aikana. Toisaalta väitöstyössä havaittiin esimerkiksi myös alkoholin nauttimisen ja henkilön taustatekijöiden yhteisvaikutuksia autonomisen hermoston säätelyyn, joita ei ole voitu aiemmin tutkia pienten tutkimuspopulaatioiden vuoksi. Kokonaisuudessaan väitöstyö osoittaa, että puettavien mittalaitteiden tuottamat arkielämän aineistot soveltuvat tieteelliseen tutkimukseen ja tulokset tukevat aiempia tutkimustuloksia, mutta tarjoavat myös uusia havaintoja sekä näkemyksiä. Tosielämän tieto voikin parantaa terveyskäyttäytymisen ja hyvinvoinnin tuntemusta, erityisesti niiltä osin, joihin perinteiset tutkimusasetelmat eivät sovellu. Käytännössä tosielämän havaintoja ja tietoa voidaan käyttää havainnollistamaan käyttäytymisen vaikutusta terveyteen ja hyvinvointiin, sekä tukemaan terveyskäyttäytymisen muutosta entistä henkilökohtaisemmin ja kohdennetummin.Wearable monitoring devices, such as smartwatches, are used for monitoring personal health, fitness, health behaviors and well-being in daily life. Nowadays, wearable devices are popular and many consumers use them, in particular, to record their physical activity and sleep. Data recorded with wearable devices is an example of real-world data that can provide practical observations and insights on health and wellness, but its analyses pose challenges for research. Consumers conduct continuous recordings with wearable devices in non-research settings. Hence, any analysis of wearable real-world monitoring data must take into account the limitations and inaccuracies of the data, as well as sampling biases and incomplete representativeness of the population that arise from the uncontrolled data collection setting. To date, there are no well-established methods for analyzing health behaviors and well-being from continuous wearable monitoring data. Consequently, real-world health monitoring data is not commonly used for research although it could provide valuable observations and insights on health behaviors and well-being. This thesis work aims at analyzing a large-scale real-world dataset of wearable heart rate variability (HRV) recordings to quantify the behaviors of physical activity (PA) and sleep that are one of the most important health behaviors. Specifically, the thesis focuses on the quantification methods and temporal patterns of PA behavior, as well as the associations that PA, alcohol intake and other lifestyles have with sleep. In addition, this thesis work aims to evaluate the feasibility to use real-world wearable monitoring data with applicable analysis methodologies for scientific research, and to demonstrate the observations and data-driven hypotheses that the results provide. The study material was an anonymized real-world HRV monitoring dataset of 52,273 Finnish employees, which was gathered and prepared by Firstbeat Technologies Oy (Jyväskylä, Finland), a Finnish company providing and developing HRV analytics for stress, recovery and exercise. The dataset included three-day continuous HRV recordings performed in free-living settings combined with self- reports of alcohol intake, work and sleep times. The recordings were originally performed for a routine wellness program (Firstbeat Lifestyle Assessment) provided for the employees by their employers as a part of preventive occupational healthcare and health promotion program. For the analysis of this thesis, PA behavior was quantified from the recordings using an HRV-based estimate of the oxygen uptake. Sleep was quantified by the regulation of the autonomic nervous system (ANS) using traditional HRV parameters and novel HRV-based indices of recovery. Both statistical and machine- learning methods were employed in the analysis for the thesis results. Temporal variations in PA behavior were observed: the amount of PA was highest at the weekends and at the beginning of the year. The amount of PA quantified by the absolute oxygen consumption was higher for men than for women, and higher for younger than older subjects, and also higher for individuals of normal weight than obese. However, PA levels were more similar between the subjects when their physical fitness level was considered in quantifying PA. Moreover, PA behavior was associated with sleep. After a day including PA, the parasympathetic regulation of the ANS and recovery during sleep were diminished, but regular PA seemed to increase parasympathetic regulation of the ANS and aid recovery during sleep. The most important predictor for ANS regulation during sleep was, however, acute alcohol intake. Acute alcohol intake dose-dependently diminished the parasympathetic regulation of the ANS and recovery during sleep, an effect that was already observable after only 1–2 standardized units of alcohol. Moreover, the same alcohol intake, normalized by the body weight, seemed to affect the ANS regulation more in younger subjects than in the older ones, but was similar for both sedentary and physically active subjects, as well as for both men and women. Many of the results obtained in this thesis accord with the findings of previous studies, such as the higher PA level on weekends, the higher amount of absolute intensity PA in men, younger and normal weight subjects, and the relationship of PA and alcohol intake with the ANS regulation during sleep. On the other hand, the results of this thesis provide new observations, for example, about the interaction between alcohol intake and subject’s background characteristics that could not have been studied before due to the limited and homogenous study populations. In conclusion, the results of this thesis demonstrates that real-world wearable monitoring data can be feasible for scientific research and its results not only supports the findings of existing studies but also provides new observations, insights and data-driven hypotheses. The real-world evidence facilitates our understanding of aspects of health behaviors and wellness that cannot be studied in the more traditional, controlled research settings. These real-world insights can be further used for designing more personalized and targeted health interventions and as tools for promoting health and well-being

The 2023 wearable photoplethysmography roadmap

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology

A wearable heart rate measurement device for children with autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by early impairment in social and communication domains and autonomic nervous system unbalance. This study evaluated heart rate (HR) as a possible indicator of stress response in children with ASD as compared to children with language disorder (LD). Twenty-four patients [mean age = 42.62 months; SD = 8.14 months,12 with ASD (10 M/2F) and 12 with LD (8 M/4F)] underwent clinical [Leiter International Performance Scale-Revised, Autism Diagnostic Observation Schedule, second edition (ADOS-2)] and physiological evaluation (HR monitoring) during five interactive activities, while wearing an HR measurement device. IQ (ASD:IQ = 103.33 ± 12.85 vs. LD:IQ = 111.00 ± 8.88, p = 0.103) and fluid reasoning on the Leiter-R Scale were within the normal range in all subjects. Increased HR during the third activity (ADOS-2 bubble play) significantly correlated with autistic symptoms (r = 0.415; p = 0.044), while correlations between ADOS-2 total score and HR during the first activity (ADOS-2 free play; r = 0.368; p = 0.077), second activity (Leiter-R figure ground subscale; r = 0.373, p = 0.073), and fifth activity (ADOS-2 anticipation of a routine with objects; r = 0.368; p = 0.076) did not quite reach statistical significance. Applying a linear regression model, we found that the ADOS-2 total score significantly influenced HR variations (p = 0.023). HR monitoring may provide a better understanding of the stress-provoking situations for children with ASD. Furthermore, it could help clinicians detect the impact of the stressful condition on the autistic core and adress treatment strategy

Psychophysiology in the digital age

The research I performed for my thesis revolved around the question how affect-physiology dynamics can be best measured in daily life. In my thesis I focused on three aspects of this question: 1) Do wearable wristband devices have sufficient validity to capture ANS activity? 2) To what extent is the laboratory design suitable to measure affect-ANS dynamics? 3) Are the affect-ANS dynamics subject to individual differences, both in the laboratory and in daily life? In chapter 2, I validated a shortened version of the Sing-a-Song Stress (SSST) test, the SSSTshort. The purpose of this test is to create social-evaluative stress in participants through a simple and brief design that does not require the involvement of multiple confederates. The results indicated that the SSSTshort was effective in inducing ANS and affective reactivity. This makes the SSSTshort a cost-effective alternative to the well-known Trier-Social-Stress task (TSST), which can be easily incorporated into large-scale studies to expand the range of stress types that can be studied in laboratory designs. In chapter 3, I validated a new wrist worn technology for measuring electrodermal activity (EDA). As expected, the overall EDA levels measured on the wrist were lower than those measured on the palm, likely due to the lower density of sweat glands on the wrist. The analysis demonstrated that the frequency measure of non-specific skin conductance response (ns.SCR) was superior to the commonly used measure of skin conductance level (SCL) for both the palm and wrist. The wrist-based ns.SCR measure was sensitive to the experimental manipulations and showed similar correspondence to the pre-ejection period (PEP) as palm-based ns.SCR. Moreover, wrist-based ns.SCR demonstrated similar predictive validity for affective state as PEP. However, the predictive validity of both wrist-based ns.SCR and PEP was lower compared to palm-based ns.SCR. These findings suggest that wrist-based ns.SCR EDA parameter has a promising future for use in psychophysiological research. In Chapter 4 of my thesis, I conducted the first study to directly compare the relationship between affect and ANS activity in a laboratory setting to that in daily life. To elicit stress in the laboratory, four different stress paradigms were employed, while stressful events in daily life were left to chance. In both settings, a valence and arousal scale was constructed from a nine-item affect questionnaire, and ANS activity was collected using the same devices. Data was collected from a single population, and the affect-ANS dynamics were analyzed using the same methodology for both laboratory and daily life settings. The results showed a remarkable similarity between the laboratory and daily life affect-ANS relationships. In Chapter 5 of my thesis, I investigated the influence of individual differences in physical activity and aerobic fitness on ANS and affective stress reactivity. Previous research has yielded inconsistent results due to heterogeneity issues in the population studied, stressor type, and the way fitness was measured. My study made a unique contribution to this field by measuring physical activity in three ways: 1) as objective aerobic fitness, 2) leisure time exercise behavior, and 3) total moderate-to-vigorous exercise (including both exercise and all other regular physical activity behaviors). In addition, we measured the physiological and affective stress response in both a laboratory and daily life setting. The total amount of physical activity showed more relationships with stress reactivity compared to exercise behavior alone, suggesting that future research should include a total physical activity variable. Our results did not support the cross-stressor adaptation hypotheses, suggesting that if exercise has a stress-reducing effect, it is unlikely to be mediated by altered ANS regulation due to repeated exposure to physical stress

An adaptive real-time intelligent system to enhance self-care of chronic disease (ARISES)

Diabetes mellitus is an increasingly prevalent chronic metabolic condition characterised by impaired glucose homeostasis and raised blood glucose levels (hyperglycaemia). Broadly categorised as either type 1 (T1DM) or type 2 diabetes (T2DM), people with diabetes are largely responsible for self-managing their blood glucose levels. Despite the development of diabetes technologies such as real time continuous glucose monitoring (RT-CGM), many individuals are frequently exposed to iatrogenic low blood glucose levels (hypoglycaemia). Severe hypoglycaemia is associated with an increased risk of recurrent hypoglycaemia, impaired symptomatic awareness of hypoglycaemia, and potentially death if left untreated. This thesis affirmed the existing clinical impact of severe hypoglycaemia and its recurrent risk in a six-month analysis of severe hypoglycaemia attended by the London Ambulance Service NHS Trust (LAS). Fewer incidents of severe hypoglycaemia observed in a date matched repeat analysis during the 2020 COVID-19 lockdown suggested improved self-management possibly motivated by a proximal fear of hospitalisation and improved structure at home. Finally, a 12-week randomised control trial demonstrating a significant difference in time spent in hypoglycaemia <3mmol/L, is the first study to prove the immediate provision of RT-CGM significantly reduces the risk of recurrent hypoglycaemia. Moreover, it highlighted the impact of socioeconomic disparity as a barrier to effective hypoglycaemia risk modification. This guided the design of an adaptive real time intelligent system to enhance self-care of chronic disease (ARISES) aimed to deliver therapeutic and lifestyle decision support for people with T1DM. The ARISES graphic user interface (GUI) design was a collaborative process conceived in a series of focus group meetings including people with T1DM. Finally, a 12-week observational study using RT-CGM, a physiological sensor wristband, and a mobile diary app, allowed for a sub-analysis identifying measurable physiological parameters associated with current and impending hypoglycaemia in people with T1DM.Open Acces

Evaluating a Personal Stress Monitoring System

Now-a-days, Life is generally much more stressful than in the past. Stress is the word that we use when we feel that we are overloaded mentally in our thoughts and wonder whether we can really cope with those placed upon us. Sometimes, stress gets us going and they are good for us but at other times, it could be the cause to undermine both our mental and physical health. The way we respond to a challenge can be considered as a kind of stress. Part of our response to a challenge is physiological and affects our own physical state. When we are faced with a challenge or a threat, our body releases some resources to protect us against them - either to get away as fast as we can, or to fight against them. This fight-or-flight response is our body\u27s sympathetic nervous system reacting to a stressful event. During this response, our body produces larger quantities of the chemicals such as cortisol, adrenaline and noradrenaline, which triggers a higher heart rate, heightened muscle preparedness, sweating, and alertness. All these factors help us to protect ourselves in a dangerous or challenging situation. But based on the frequency of stress facing by a person, these changes may affect his or her health negatively. In order to evaluate an individual\u27s stress, I worked on this thesis in developing a personal stress monitoring system to capture the stress undergoing by an individual in his or her daily life

Treat me well : affective and physiological feedback for wheelchair users

This work reports a electrocardiograph and skin conductivity hardware architecture, based on E-textile electrodes, attached to a wheelchair for affective and physiological computing. Appropriate conditioning circuits and a microcontroller platform that performs acquisition, primary processing, and communication using Bluetooth were designed and implemented. To increase the accuracy and repeatability of the skin conductivity measuring channel, force measurement sensors were attached to the system certifying measuring contact force on the electrode level. Advanced processing including Rwave peak detector, adaptive filtering and autonomic nervous system analysis based on wavelets transform was designed and implemented on a server. A central design of affective recognition and biofeedback system is described.Fundação para a Ciência e a Tecnologia (FCT