Cyclist Performance Classification System based on Submaximal Fitness Test

Performances among cyclist always measured by time traveled from start to finish line and then the winner in cycling event also decided by time or who crossed the finish line first. On the other hand, cyclist performance can be measured through cardiorespiratory and physical fitness, and this performance can be enhanced by proper training to increase fitness and skill without burden. A wireless sensor network (WSN) system developed by combined various sensing element to capture physiological and bicycle’s kinetics feedback. Physiological data such as heart rate variability (HRV) and kinetic data such as paddling power and cadence used as input in Astrand-Ryhming and PWC150 submaximal test to classify the performance group among cyclist. Developed HRV system using Photoplethysmography (PPG) provides the significant output with R2 value was 0.967. A group of 15 cyclists from three different backgrounds was used as a subject in this study. Maximal oxygen intake (VO2max) produced by AstrandRyhming test correlated with estimated paddling power produced by PWC150 test with P<0.01 and the R2 value was 0.8656. Discriminant analysis was 88.3% successfully classified cyclist into 3 group and group of trained and untrained cyclist clearly separated

A multi-channel opto-electronic sensor to accurately monitor heart rate against motion artefact during exercise

This study presents the use of a multi-channel opto-electronic sensor (OEPS) to effectively monitor critical physiological parameters whilst preventing motion artefact as increasingly demanded by personal healthcare. The aim of this work was to study how to capture the heart rate (HR) efficiently through a well-constructed OEPS and a 3-axis accelerometer with wireless communication. A protocol was designed to incorporate sitting, standing, walking, running and cycling. The datasets collected from these activities were processed to elaborate sport physiological effects. t-test, Bland-Altman Agreement (BAA), and correlation to evaluate the performance of the OEPS were used against Polar and Mio-Alpha HR monitors. No differences in the HR were found between OEPS, and either Polar or Mio-Alpha (both p > 0.05); a strong correlation was found between Polar and OEPS (r: 0.96, p < 0.001); the bias of BAA 0.85 bpm, the standard deviation (SD) 9.20 bpm, and the limits of agreement (LOA) from −17.18 bpm to +18.88 bpm. For the Mio-Alpha and OEPS, a strong correlation was found (r: 0.96, p < 0.001); the bias of BAA 1.63 bpm, SD 8.62 bpm, LOA from −15.27 bpm to +18.58 bpm. These results demonstrate the OEPS to be capable of carrying out real time and remote monitoring of heart rate

Review of wireless sensors networks in health applications

Wireless Sensor Networks (WSN) are becoming increasingly important for telemedicine applications, monitoring patients both in the clinical setting and at home. They reduce user discomfort, enhance mobility and reduce costs. WSN are also fundamental in Ambient Assisted Living (AAL) since these smart systems, which are tailored to users needs, collect information about users and their ambient in order to provide personalized feedback. Despite the growing use of wireless communications in the health domain and in AAL systems there is a lack of research literature reviewing trials of these technologies. This paper provides a systematic review of the use of WSN in the health domain, presenting current WSN implementations. It covers 126 papers, of which 26 are studies, classified according to inclusion criteria. There is presented a discussion about the recent research conducted in the field.Junta de Andalucía p08-TIC-363

PERANCANGAN SISTEM PENDETEKSI DENYUT NADI MENGGUNAKAN METODE EULERIAN MOTION MAGNIFICATION

Detak jantung merupakan parameter yang sangat penting dalam menentukan kesehatan seseorang. Dari detak jantung, dapat diketahui seseorang memiliki gangguan kesehatan atau tidak. Saat ini, pengukuran detak jantung dilakukan dengan menggunakan sensor pulse oximetry yang dijepitkan di ujung jari atau daun telinga. ECG juga dapat digunakan untuk mengukur detak jantung, alat ini mengharuskan pasien memakai patch di dada yang dapat menimbulkan rasa tidak nyaman, bahkan dapat menyebabkan iritasi. Baru-baru ini dikembangkan sebuah metode bernama Eulerian Motion Magnification. Pada penelitian sebelumnya metode ini telah diterapkan untuk mengukur detak jantung dengan cara mengambil video dari wajah pasien, kemudian diamati perubahan warna wajah saat jantung memompa darah ke kepala. Dalam tugas akhir ini, metode tersebut digunakan untuk mengukur detak jantung dengan cara mengambil video dari pergelangan tangan. Pergerakan mikro dalam video tersebut kemudian diperbesar sehingga denyut nadi dapat terlihat. Setelah itu dilakukan deteksi pada denyut nadi yang telah terlihat. Kemudian didapatkan hasil berupa jumlah denyut nadi per menit dalam satuan BPM. Hasil pengujian sistem pada tugas akhir ini menunjukkan bahwa metode Eulerian Motion Magnification menghasilkan nilai akurasi tertinggi yaitu 95,83% dengan waktu komputasi 338 detik. Hasil tersebut didapat pada kondisi intensitas cahaya 1358 lux, resolusi video 1280x720 piksel, jarak pengambilan video 10 cm, dan frame rate 25 fps. Kata kunci : Pulse Oximetry Sensor, ECG, Eulerian Motion Magnificatio

Sensing with Earables: A Systematic Literature Review and Taxonomy of Phenomena

Earables have emerged as a unique platform for ubiquitous computing by augmenting ear-worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new research exploring what can be detected on a wearable, small form factor. As a sensing platform, the ears are less susceptible to motion artifacts and are located in close proximity to a number of important anatomical structures including the brain, blood vessels, and facial muscles which reveal a wealth of information. They can be easily reached by the hands and the ear canal itself is affected by mouth, face, and head movements. We have conducted a systematic literature review of 271 earable publications from the ACM and IEEE libraries. These were synthesized into an open-ended taxonomy of 47 different phenomena that can be sensed in, on, or around the ear. Through analysis, we identify 13 fundamental phenomena from which all other phenomena can be derived, and discuss the different sensors and sensing principles used to detect them. We comprehensively review the phenomena in four main areas of (i) physiological monitoring and health, (ii) movement and activity, (iii) interaction, and (iv) authentication and identification. This breadth highlights the potential that earables have to offer as a ubiquitous, general-purpose platform

Sensing with Earables: A Systematic Literature Review and Taxonomy of Phenomena

Earables have emerged as a unique platform for ubiquitous computing by augmenting ear-worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new research exploring what can be detected on a wearable, small form factor. As a sensing platform, the ears are less susceptible to motion artifacts and are located in close proximity to a number of important anatomical structures including the brain, blood vessels, and facial muscles which reveal a wealth of information. They can be easily reached by the hands and the ear canal itself is affected by mouth, face, and head movements. We have conducted a systematic literature review of 271 earable publications from the ACM and IEEE libraries. These were synthesized into an open-ended taxonomy of 47 different phenomena that can be sensed in, on, or around the ear. Through analysis, we identify 13 fundamental phenomena from which all other phenomena can be derived, and discuss the different sensors and sensing principles used to detect them. We comprehensively review the phenomena in four main areas of (i) physiological monitoring and health, (ii) movement and activity, (iii) interaction, and (iv) authentication and identification. This breadth highlights the potential that earables have to offer as a ubiquitous, general-purpose platform

Happisaturaation mittaaminen puettavilla laitteilla

Veren happisaturaatio on tärkeä fysiologinen parametri, joka kuvaa veressä olevan hapen määrää ja antaa tärkeää tietoa kudosten hapensaannista. Happisaturaatio voidaan määrittää fotopletysmografiamittauksen (engl. photoplethysmography, PPG) avulla. Usein happisaturaatio mitataan sormenpäähään kiinnitettävällä pulssioksimetrilla, joka rajoittaa käyttäjän normaaleja toimintoja. Käyttäjää häiritsemättömät puettavat laitteet, kuten älykellot ja -sormukset, tarjoavat uusia mahdollisuuksia happisaturaation mittaamiseen. Tämän työn tavoitteena on esitellä puettavilla laitteilla toteutettavien happisaturaatiomittauksien mahdollisia anturiratkaisuja, mittauksiin liittyviä haasteita ja tulevaisuudennäkymiä. Happisaturaatiota mittaavissa puettavissa laitteissa voidaan hyödyntää erilaisia anturiratkaisuja. Erilaisilla anturiratkaisuilla pyritään mittaamaan mahdollisimman hyvälaatuista PPG-signaalia sovelluskohteeseen parhaiten soveltuvalla tavalla. PPG-mittauksessa voidaan vaikuttaa esimerkiksi mittauspaikan valintaan tai PPG-anturissa käytettäviin ratkaisuihin, kuten valonlähteen ja valoanturin sijoitteluun toisiinsa nähden. Tällä hetkellä happisaturaatiota on mahdollista mitata vain harvoilla puettavilla laitteilla, sillä mittauksiin liittyy useita ratkaisemattomia haasteita. PPG-signaaliin aiheutuu esimerkiksi helposti liikeartefaktaa eli mittausanturin liikkumisesta aiheutuvaa kohinaa. Lisäksi anturin mittauspaikkaan kohdistaman voiman tulee olla sopiva, jotta mitattava signaali olisi hyvälaatuista. Yksilöiden väliset erot esimerkiksi ihonvärissä tai painoindeksissä aiheuttavat myös vaihtelevuutta mittaustuloksiin. Jos nämä haasteet onnistutaan ratkaisemaan, tulevaisuudessa puettavilla laitteilla toteutettavaa happisaturaatiomittausta voitaisiin käyttää useissa sovelluskohteissa. Puettavilla laitteilla toteutettava happisaturaatiomittaus mahdollistaa ajasta ja paikasta riippumattoman jatkuva-aikaisen monitoroinnin. Ajasta ja paikasta riippumattoman monitoroinnin ansiosta joitakin kliinisessä ympäristössä aikaa vieviä tutkimuksia, kuten unen seurantaa, voitaisiin tulevaisuudessa toteuttaa mahdollisesti myös kotioloissa. Erityisesti keuhkosairauksia sairastavat potilaat voisivat hyötyä jatkuva-aikaisesta happisaturaation mittaamisesta kotioloissa, sillä keuhkosairauksia sairastavilla potilailla happisaturaatiolukemat voivat olla sairauden vuoksi normaalia matalampia