Search results for "Wearable computer"

showing 10 items of 60 documents

Artificial Intelligence in Medicine: Today and Tomorrow

2020

Artificial intelligence-powered medical technologies are rapidly evolving into applicable solutions for clinical practice. Deep learning algorithms can deal with increasing amounts of data provided by wearables, smartphones, and other mobile monitoring sensors in different areas of medicine. Currently, only very specific settings in clinical practice benefit from the application of artificial intelligence, such as the detection of atrial fibrillation, epilepsy seizures, and hypoglycemia, or the diagnosis of disease based on histopathological examination or medical imaging. The implementation of augmented medicine is long-awaited by patients because it allows for a greater autonomy and a mor…

digital medicineComputer sciencemedia_common.quotation_subjectWearable computerScientific literature030204 cardiovascular system & hematology03 medical and health sciences0302 clinical medicineHealth careMedical imaging030212 general & internal medicinemobile healthmedia_commonmedical technologieslcsh:R5-920business.industryGénéralitésGeneral MedicineBioethicsartificial intelligenceClinical trialmonitoringPerspectiveMedicineArtificial intelligenceApplications of artificial intelligencebusinesslcsh:Medicine (General)AutonomyFrontiers in Medicine
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Dog behaviour classification with movement sensors placed on the harness and the collar

2021

Dog owners’ understanding of the daily behaviour of their dogs may be enhanced by movement measurements that can detect repeatable dog behaviour, such as levels of daily activity and rest as well as their changes. The aim of this study was to evaluate the performance of supervised machine learning methods utilising accelerometer and gyroscope data provided by wearable movement sensors in classification of seven typical dog activities in a semi-controlled test situation. Forty-five middle to large sized dogs participated in the study. Two sensor devices were attached to each dog, one on the back of the dog in a harness and one on the neck collar. Altogether 54 features were extracted from th…

dogsaktiivisuusComputer scienceWearable computerAccelerometer413 Veterinary science01 natural sciencesCollarlaw.inventionCanine0403 veterinary scienceFood AnimalsSniffinglawAccelerometryDogälyvaatteetComputer vision412 Animal science dairy science318 Medical biotechnologyMovement (music)Wearable technologyGyroscope04 agricultural and veterinary sciencesliikkeentunnistuskoneoppiminenbehaviour classificationActivity monitoringeläimeteläinten koulutusactivity monitoringBehaviour classification040301 veterinary sciencesaktigrafiacanineSittingkoiraeläinten käyttäytyminenwearable technologyACCELEROMETERClassifier (linguistics)MEASURED PHYSICAL-ACTIVITYaccelerometrypuettava teknologiaVALIDITYkäyttäytyminenbusiness.industry010401 analytical chemistryANIMALS113 Computer and information sciencesActigraphy0104 chemical sciencesACCELERATION DATAkoulutusmittarit (mittaus)Animal Science and ZoologyArtificial intelligencebusinessactigraphy
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Consumer wearable technologies to identify and monitor exercise-related arrhythmias in athletes

2020

PURPOSE OF REVIEW: The aim of this study was to synthesize the current evidence supporting and against the use of wearable devices to detect underlying heart conditions in athletes and the most significant limitations. RECENT FINDINGS: Although several large studies have been conducted to evaluate the ability of wearables devices to identify atrial fibrillation among the general population, no studies evaluating their ability to detect other exercise-related arrhythmias in athletes are very sparse. Most of the studies or case reports are focused on the wearables' reliability and accuracy compared with standard ECG. Only small studies evaluating the accuracy of one wearable device in athlete…

education.field_of_studymedicine.medical_specialtybiologybusiness.industryAthletesPopulationWearable computer030204 cardiovascular system & hematologybiology.organism_classification03 medical and health sciences0302 clinical medicinePhysical medicine and rehabilitationMedicineDiagnostic data030212 general & internal medicineCardiology and Cardiovascular MedicinebusinesseducationWearable technologyStandard ECGHealthcare systemCurrent Opinion in Cardiology
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Wearable Sensor for Assessing Gait and Postural Alterations in Patients with Diabetes: A Scoping Review.

2021

Background and Objectives: Diabetes mellitus is considered a serious public health problem due to its high prevalence and related complications, including gait and posture impairments due to neuropathy and vascular alterations and the subsequent increased risk of falls. The gait of patients with diabetes is characterized by alterations of the main spatiotemporal gait parameters such as gait velocity, cadence, stride time and length, which are also known to worsen with disease course. Wearable sensor systems can be used for gait analysis by providing spatiotemporal parameters and postural control (evaluated from the perspective of body sway), useful for investigating the disease progression.…

medicine.medical_specialtyMedicine (General)inertial sensorSTRIDEWearable computerwearable deviceReviewwearable sensorDiabetegaitWearable Electronic DevicesGait (human)Physical medicine and rehabilitationR5-920Diabetes mellitusDiabetes MellitusMedicineHumansIn patientPostural Balanceposturediabetesbusiness.industryGeneral Medicinemedicine.diseaseGait analysisMedline databasebusinessCadenceGait Analysishuman activitiesMedicina (Kaunas, Lithuania)
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SenseCam: A new tool for memory rehabilitation?

2016

International audience; The emergence of life-logging technologies has led neuropsychologist to focus on understanding how this new technology could help patients with memory disorders. Despite the growing number of studies using life-logging technologies, a theoretical framework supporting its effectiveness is lacking. This review focuses on the use of life-logging in the context of memory rehabilitation, particularly the use of SenseCam, a wearable camera allowing passive image capture. In our opinion, reviewing SenseCam images can be effective for memory rehabilitation only if it provides more than an assessment of prior occurrence in ways that reinstates previous thoughts, feelings and …

medicine.medical_treatmentWearable computerContext (language use)[ SCCO.PSYC ] Cognitive science/Psychology050105 experimental psychology03 medical and health sciences0302 clinical medicineAlzheimer DiseaseMemorymedicineMemory impairmentHumans0501 psychology and cognitive sciencesEpisodic memoryMemory DisordersRehabilitationRecallbusiness.industryBrain lesions[SCCO.NEUR]Cognitive science/Neuroscience05 social sciencesRehabilitationUsabilitySenseCamAlzheimer's diseaseNeurologyIf and only ifMental Recall[ SCCO.NEUR ] Cognitive science/Neuroscience[SCCO.PSYC]Cognitive science/PsychologyNeurology (clinical)Psychologybusiness030217 neurology & neurosurgeryCognitive psychology
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Use of accelerometers and gyros for hip and knee angle estimation

2013

In this paper a wearable sensor system, consisting of accelerometers and gyros, has been studied to estimate hip and knee angles. The proposed algorithm, developed in order to avoid the error accumulation due to gyroscopes drift, has been tested on angle measurement of the hip and knee of a commercial device for assisted gait. The results have shown a good accuracy of the angles estimation, also in high angle rate movement

musculoskeletal diseasesSensor systemEngineeringbusiness.industryAcousticsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONKnee angleWearable computerGyroscopeAccelerometerlaw.inventionAccelerometers Gyroscopes Estimation Knee Joints Hip SensorsGait (human)Settore ING-INF/04 - AutomaticalawGait analysisElectronic engineeringHigh anglebusinesshuman activitiesComputingMethodologies_COMPUTERGRAPHICS2013 IEEE International Conference on Mechatronics and Automation
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Emotions and Activity Recognition System Using Wearable Device Sensors

2021

Nowadays machines have become extremely smart, there are a lot of existing services that seemed to be unexpectable and futuristic decades or even a few years ago. However, artificial intelligence is still far from human intelligence, machines do not have feelings, consciousness, and intuition. How can we help machines to learn about human feelings and understand their needs better? People take their devices wherever they go, what can devices tell us about their owners? Personal preferences and needs are dependent on emotional and situational contexts. Therefore, emotional and activity aware gadgets would be more intuitive and provide more appropriate information to users. Contemporary weara…

paikkatiedotComputer sciencemedia_common.quotation_subjectWearable computertekoälyRecommender systemwearable device sensorslcsh:TelecommunicationActivity recognitiontoimintatunteetHuman–computer interactionlcsh:TK5101-6720emotions recognitionzero-shot semantic segmentationactivity recognitionanturitSituational ethicsimage segmentationWearable technologymedia_commonHuman intelligencebusiness.industrymielialadeep learningliikkeentunnistusmachine learningkoneoppiminenälytuotteetFeelingälytekniikkaConsciousnessbusinesskasvontunnistus (tietotekniikka)fyysinen aktiivisuus2021 28th Conference of Open Innovations Association (FRUCT)
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P4Well Concept to Empower Self-Management of Psychophysiological Wellbeing and Load Recovery

2009

Chronic health problems related to mental wellbeing are rapidly growing, calling for novel solutions focusing on individual as a psychophysiological being. We describe a novel technology-based concept for empowering citizen towards holistic self-management of her wellbeing: “P4Well” (Pervasive Personal and PsychoPhysiological management of WELLness). The primary focus of the concept is on management of stress and recovery from stress caused by daily life through improved health management strategies. The P4Well concept combines modern psychological methods with personal health technologies. The technologies include a web-portal and web-based tools, mobile phone with mobile client applicatio…

self-managementSelf-managementKnowledge managementHealth management systemexercisebusiness.industryInterpretation (philosophy)personal health systemsWearable computermini-interventionstressMobile phoneHealth careSocial mediapsychologicalMobile telephonysleepPsychologybusiness
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Improving Energy Expenditure Estimation in Wrist-Worn Wearables by Augmenting Heart Rate Data With Heat Flux Measurement

2021

Wearable electronics are often used for estimating the energy expenditure of the user based on heart rate measurement. While heart rate is a good predictor of calorie consumption at high intensities, it is less precise at low intensity levels, which translates into inaccurate results when estimating daily net energy expenditure. In this study, heart rate measurement was augmented with heat flux (HF) measurement, a form of direct calorimetry. A physical exercise test on a group of 15 people showed that HF measurement can improve the accuracy of calorie consumption estimates especially during rest and low-intensity activity when used in conjunction with heart rate information and vital backgr…

sykeCalorieComputer sciencebusiness.industry020208 electrical & electronic engineeringWearable computerPhysical exercise02 engineering and technologyIntensity (physics)ruumiinlämpömittaustekniikkaEnergy expenditureHeat fluxHeart rateStatistics0202 electrical engineering electronic engineering information engineeringanturitElectrical and Electronic EngineeringbusinessInstrumentationenergiankulutus (aineenvaihdunta)Wearable technologyIEEE Transactions on Instrumentation and Measurement
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Fall Detection Using Location Sensors and Accelerometers

2015

The rapid aging of the world's population is driving the development of pervasive solutions for elder care. These solutions, which often involve fall detection with accelerometers, are accurate in laboratory conditions but can fail in some real-life situations. To overcome this, the authors present the Confidence system, which detects falls mainly with location sensors. A user wears one to four tags. By detecting tag locations with sensors, the system can recognize the user's activity, such as falling and then lying down afterward, as well as the context in terms of the location in the home. The authors used a scenario consisting of events difficult to recognize as falls or nonfalls to comp…

ta113education.field_of_studyContext modelUbiquitous computingaccelerometersaccuracyComputer sciencePopulationReal-time computingagingWearable computerContext (language use)ta3141accelerationAccelerometersensorsComputer Science ApplicationscontextComputational Theory and MathematicsFalling (sensation)educationLyingSoftwareSimulationsenior citizensIEEE Pervasive Computing
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