A digital ASIC chip customized for battery-operated body sensing devices is presented.The ASIC incorporates a novel hybrid-architecture fast Fourier transform(FFT) unit that is capable of scalable spectral analysis,a licensed ARM7TDMI IP hardcore and several peripheral IP blocks.Extensive experimental results suggest that the complete chip works as intended.The power consumption of the FFT unit is 0.69 mW @ 1 MHz with 1.8 V power supply.The low-power and programmable features of the ASIC make it suitable for’on-the-fly’ low-frequency physiological signal processing.
The study of three-dimensional human kinematics has significant impacts on medical and healthcare technology innovations. As a non-invasive technology, optoelectronic stereophotogrammetry is widely used for in-vivo locomotor evaluations. However, relatively high testing difficulties, poor testing accuracies, and high analysis complexities prohibit its further employment. The objective of this study is to explore an improved modeling technique for quantitative measurement and analysis of human locomotion. Firstly, a 3D whole body model of 17 rigid segments was developed to describe human locomotion. Subsequently, a novel infrared reflective marker cluster for 17 body segments was constructed to calibrate and record the 3D segmental position and orientation of each functional body region simultaneously with high spatial accuracy. In addition, the novel calibration procedure and the conception of kinematic coupling of human locomotion were proposed to investigate the segmental functional characteristics of human motion. Eight healthy male subjects were evaluated with walking and running experiments using the Qualisys motion capture system. The experimental results demonstrated the followings: (i) The kinematic coupling of the upper limbs and the lower limbs both showed the significant characteristics of joint motion, while the torso motion of human possessed remarkable features of segmental motion; (ii) flexion/extension was the main motion feature in sagittal plane, while the lateral bending in coronal plane and the axial rotation in transverse plane were subsidiary motions during an entire walking cycle regarding to all the segments of the human body; (iii) compared with conventional methods, the improved techniques have a competitive advantage in the convenient measurement and accurate analysis of the segmental dynamic functional characteristics during human locomotion. The modeling technique proposed in this paper has great potentials in rehabilitation engineering as well as ergonomics and biomimetic engineering
Respiratory monitoring is increasingly used in clinical and healthcare practices to diagnose chronic cardio-pulmonary functional diseases during various routine activities.Wearable medical devices have realized the possibilities of ubiquitous respiratory monitoring,however,relatively little attention is paid to accuracy and reliability.In previous study,a wearable respiration biofeedback system was designed.In this work,three kinds of signals were mixed to extract respiratory rate,i.e.,respiration inductive plethysmography(RIP),3D-acceleration and ECG.In-situ experiments with twelve subjects indicate that the method significantly improves the accuracy and reliability over a dynamic range of respiration rate.It is possible to derive respiration rate from three signals within mean absolute percentage error 4.37%of a reference gold standard.Similarly studies derive respiratory rate from single-lead ECG within mean absolute percentage error 17%of a reference gold standard.
