Research And System Implementation On Multi-parameter Measurement For Wearable Smart Mobile Healthcare

As an approach to health assessment,mobile healthcare devices have significant values on research and application.Traditional monitoring equipment and methods are usually affected by the restrictions of wearing methods and environmental factors,which means they are not suitable for daily use.With the development of wearable technology,mobile healthcare research and products based on this technology are gradually integrated into daily life.However,there are still several issues such as measuring accuracy,device stability and system integrity.This dissertation aims to study the key techniques of multi-parameter extraction in wearable healthcare.Meanwhile,a smart mobile healthcare system based on the proposed methods is designed and implemented for daily healthcare.The main work and achievements of this thesis are described as follows.Comprised of four steps named signal preprocessing,motion state decision,singular spectrum anslysis(SSA)and frequency selection,a motion-based heart rate measurement method based on reflective photoplethysmography(PPG)signals is proposed.The method has been experimentally verified.The correlation coefficient between the estimation and reference was 0.985,and the mean absolute error was 2.33 beats per minute(BPM).The results have revealed the effectiveness on heart rate monitoring in motion status.Two approaches to blood pressure measurement based on pulse transit time(PTT)are proposed.Dual-channel PPG signals and SSA are adopted in the first approach to achieve peripheral PTT(PPTT)measurements in motion status.A model-based blood pressure measurement is achieved based on the PPTT.The method has been experimentally verified.The correlation coefficients were 0.75 and 0.77 for systolic blood pressure(SBP)and diastolic blood pressure(DBP)estimation,respectively.The mean absolute errors were5.91 mm Hg and 5.13 mm Hg,respectively.The second approach uses Seismo-cardiography(SCG)and PPG to achieve PTT.Then blood pressure measurement is realized based on the PTT and a data-driven method named LANDMARC.The correlation coefficients were 0.80 and 0.76 for SBP and DBP estimation,respectively.The mean absolute errors were 5.11 mm Hg and 4.74 mm Hg,respectively.The experimental results have indicated that both PTT-based approaches can be used for cuff-less blood pressure measurement.The first approach with motion interference suression is suitable for motion state,and the second can be applied in relatively static environment due to the high measuring accuracy.A method for plantar health condition evaluation based on exercise load quantification and plantar pressure distribution is proposed.Firstly,heart rate and strike frequency are used to quantify the exercise load.Secondly,plantar health assessment is achieved based the quantification and plantar pressure distribution.The method has been experimentally examined,and the results have shown the effectiveness on plantar symptoms detection.The severity of the symptom has been also quantified,and the results have revealed the coherence with the actual situations.A smart mobile healthcare system,including a wearable smart healthcare terminal device and a remote health monitoring server,is designed and implemented.The healthcare terminal device is comprised of a wearable multi-parameter measuring device and a mobile client.The measuring device can be used to acquire the signals of Electrocardiogram(ECG),PPG,acceleration and plantar pressure.At the same time,it is also designed for the monitoring of heart rate,blood oxygen saturation,blood pressure and plantar health condition.The mobile client can be adopted for not only physiological data display and uploading,but also instant messaging and emergency handling.The server platform used by the doctor is comprised of a database and a control terminal.The database is mainly used for the storage of user data and transport protocols with the mobile client and the control terminal.The control terminal is realized for the query of user data and the acceptance of health consultation.Meanwhile,it can be used to receive user location and real-time physiological data under emergency conditions.