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Physical Activity Recognition Utilizing the Built-In Kinematic Sensors of a Smartphone

Physical activity (PA) recognition has recently become important in activity monitoring for the public healthcare. Although body-worn sensors are well suited to collect data on activity patterns for long periods of time, users may forget to wear special microsensors. On the contrary, more and more people take smartphone with them almost anytime. At present, most popular smartphones have three built-in kinematic sensors (triaccelerometer, gyroscope, and magnetic sensor) which could be utilized to recognize PA. This study utilized three built-in kinematic sensors in a smartphone to recognize PA and found out which features derived from the three sensors were significant to different PA. We used a combined algorithm of Fishers discriminant ratio criterion and J 3 criterion for feature selection. A hierarchical classifiers system including fourteen classifiers was proposed and employed to recognize fifteen activities. The optimal features derived from the built-in kinematic sensors of the smartphone were selected from 140 features. The results indicated that the accelerometer was significant to PA recognition, while gyroscope and orientation sensor were effective to recognize the change of body posture and detect falls, respectively. The total classification accuracy of 95.03% demonstrated the feasibility of utilizing the built-in kinematic sensors of the smartphone to recognize PA.

Fall detection by built-in tri-accelerometer of smartphone

In this study, a fall detection system based on the data acquired from a waist-mounted smartphone has been developed in a real-time environment. The built-in tri-accelerometer was utilized to collect the information about body movement. At the same time, the smartphone is able to classify the data for activity recognition. Body motion can be classified into five different patterns, i.e. vertical activity, lying, sitting or static standing, horizontal activity and fall. If a fall is suspected, an automatic Multimedia Messaging Service (MMS) will be sent to pre-selected people, with information including the time, GPS coordinate, and Google map of suspected fall location. The major advantage of the proposed system is the use of smartphone which is readily available to most people.

A Wearable Context-Aware ECG Monitoring System Integrated with Built-in Kinematic Sensors of the Smartphone

Continuously monitoring the ECG signals over hours combined with activity status is very important for preventing cardiovascular diseases. A traditional ECG holter is often inconvenient to carry because it has many electrodes attached to the chest and because it is heavy. This work proposes a wearable, low power context-aware ECG monitoring system integrated built-in kinetic sensors of the smartphone with a self-designed ECG sensor. The wearable ECG sensor is comprised of a fully integrated analog front-end (AFE), a commercial micro control unit (MCU), a secure digital (SD) card, and a Bluetooth module. The whole sensor is very small with a size of only 58 × 50 × 10 mm for wearable monitoring application due to the AFE design, and the total power dissipation in a full round of ECG acquisition is only 12.5 mW. With the help of built-in kinetic sensors of the smartphone, the proposed system can compute and recognize user’s physical activity, and thus provide context-aware information for the continuous ECG monitoring. The experimental results demonstrated the performance of proposed system in improving diagnosis accuracy for arrhythmias and identifying the most common abnormal ECG patterns in different activities. In conclusion, we provide a wearable, accurate and energy-efficient system for long-term and context-aware ECG monitoring without any extra cost on kinetic sensor design but with the help of the widespread smartphone.

Sensory and optogenetically driven single-vessel fMRI

Magnetic resonance imaging (MRI) sensitivity approaches vessel specificity. We developed a single-vessel functional MRI (fMRI) method to image the contribution of vascular components to blood oxygenation level–dependent (BOLD) and cerebral blood volume (CBV) fMRI signal. We mapped individual vessels penetrating the rat somatosensory cortex with 100-ms temporal resolution by MRI with sensory or optogenetic stimulation. The BOLD signal originated primarily from venules, and the CBV signal from arterioles. The single-vessel fMRI method and its combination with optogenetics provide a platform for mapping the hemodynamic signal through the neurovascular network with specificity at the level of individual arterioles and venules.

Identifying typical physical activity on smartphone with varying positions and orientations

BackgroundTraditional activity recognition solutions are not widely applicable due to a high cost and inconvenience to use with numerous sensors. This paper aims to automatically recognize physical activity with the help of the built-in sensors of the widespread smartphone without any limitation of firm attachment to the human body.MethodsBy introducing a method to judge whether the phone is in a pocket, we investigated the data collected from six positions of seven subjects, chose five signals that are insensitive to orientation for activity classification. Decision trees (J48), Naive Bayes and Sequential minimal optimization (SMO) were employed to recognize five activities: static, walking, running, walking upstairs and walking downstairs.ResultsThe experimental results based on 8,097 activity data demonstrated that the J48 classifier produced the best performance with an average recognition accuracy of 89.6% during the three classifiers, and thus would serve as the optimal online classifier.ConclusionsThe utilization of the built-in sensors of the smartphone to recognize typical physical activities without any limitation of firm attachment is feasible.

Brain-state dependent astrocytic Ca2+ signals are coupled to both positive and negative BOLD-fMRI signals

Significance The role of astrocytes on brain function is controversial in many aspects. It remains challenging to specify the in vivo functional impact of astrocytic calcium signal when mediating vasodilation/constriction at varied physiological or pathophysiological conditions. Here, we applied simultaneous fMRI and GCaMP-mediated Ca2+ optical fiber recording to detect distinct astrocytic Ca2+ signals (evoked vs. intrinsic) coupled to positive and negative blood-oxygen-level-dependent signals, respectively and concurrently, with unique spatial and temporal patterns. Not only did we demonstrate the distinct neurovascular coupling events coupled to the evoked and intrinsic astrocytic calcium signals, but also revealed the thalamic regulation mechanism underlying the astrocytic calcium-mediated brain state switch. This astrocytic-relevant regulatory mechanism could underlie numerous brain disorder and injury models relevant to gliovascular disruption. Astrocytic Ca2+-mediated gliovascular interactions regulate the neurovascular network in situ and in vivo. However, it is difficult to measure directly both the astrocytic activity and fMRI to relate the various forms of blood-oxygen-level-dependent (BOLD) signaling to brain states under normal and pathological conditions. In this study, fMRI and GCaMP-mediated Ca2+ optical fiber recordings revealed distinct evoked astrocytic Ca2+ signals that were coupled with positive BOLD signals and intrinsic astrocytic Ca2+ signals that were coupled with negative BOLD signals. Both evoked and intrinsic astrocytic calcium signal could occur concurrently or respectively during stimulation. The intrinsic astrocytic calcium signal can be detected globally in multiple cortical sites in contrast to the evoked astrocytic calcium signal only detected at the activated cortical region. Unlike propagating Ca2+ waves in spreading depolarization/depression, the intrinsic Ca2+ spikes occurred simultaneously in both hemispheres and were initiated upon the activation of the central thalamus and midbrain reticular formation. The occurrence of the intrinsic astrocytic calcium signal is strongly coincident with an increased EEG power level of the brain resting-state fluctuation. These results demonstrate highly correlated astrocytic Ca2+ spikes with bidirectional fMRI signals based on the thalamic regulation of cortical states, depicting a brain-state dependency of both astrocytic Ca2+ and BOLD fMRI signals.

Ultra-Slow Single-Vessel BOLD and CBV-Based fMRI Spatiotemporal Dynamics and Their Correlation with Neuronal Intracellular Calcium Signals

Functional MRI has been used to map brain activity and functional connectivity based on the strength and temporal coherence of neurovascular-coupled hemodynamic signals. Here, single-vessel fMRI reveals vessel-specific correlation patterns in both rodents and humans. In anesthetized rats, fluctuations in the vessel-specific fMRI signal are correlated with the intracellular calcium signal measured in neighboring neurons. Further, the blood-oxygen-level-dependent (BOLD) signal from individual venules and the cerebral-blood-volume signal from individual arterioles show correlations at ultra-slow (<0.1xa0Hz), anesthetic-modulated rhythms. These data support a model that links neuronal activity to intrinsic oscillations in the cerebral vasculature, with a spatial correlation length of ∼2xa0mm for arterioles. In complementary data from awake human subjects, the BOLD signal is spatially correlated among sulcus veins and specified intracortical veins of the visual cortex at similar ultra-slow rhythms. These data support the use of fMRI to resolve functional connectivity at the level of single vessels.

Two-photon and fMRI measurements of activity dependent single vessel dynamics in mouse

I will discuss recent two-photon optical and high-field functional MRI measurements that link brain activity with changes in cortical arteriole and venule diameter. The data support a “Bagpipe” model (Drew et al PNAS 2011) in which arterioles dilate upon heightened intrinsic or stimulus-driven neuronal activity and form a reservoir of blood to perfuse cortex. Implications and extensions of this result will be discussed.