Features for matching people in different views

There have been significant advances in the computer vision field during the last decade. During this period, many methods have been developed that have been successful in solving challenging problems including Face Detection, Object Recognition and 3D Scene Reconstruction. The solutions developed by computer vision researchers have been widely adopted and used in many real-life applications such as those faced in the medical and security industry. Among the different branches of computer vision, Object Recognition has been an area that has advanced rapidly in recent years. The successful introduction of approaches such as feature extraction and description has been an important factor in the growth of this area. In recent years, researchers have attempted to use these approaches and apply them to other problems such as Content Based Image Retrieval and Tracking. In this work, we present a novel system that finds correspondences between people seen in different images. Unlike other approaches that rely on a video stream to track the movement of people between images, here we present a feature-based approach where we locate a target’s new location in an image, based only on its visual appearance. Our proposed system comprises three steps. In the first step, a set of features is extracted from the target’s appearance. A novel algorithm is developed that allows extraction of features from a target that is particularly suitable to the modelling task. In the second step, each feature is characterised using a combined colour and texture descriptor. Inclusion of information relating to both colour and texture of a feature add to the descriptor’s distinctiveness. Finally, the target’s appearance and pose is modelled as a collection of such features and descriptors. This collection is then used as a template that allows us to search for a similar combination of features in other images that correspond to the target’s new location. We have demonstrated the effectiveness of our system in locating a target’s new position in an image, despite differences in viewpoint, scale or elapsed time between the images. The characterisation of a target as a collection of features also allows our system to robustly deal with the partial occlusion of the target

Trust in Construction AI-Powered Collaborative Robots: A Qualitative Empirical Analysis

Construction technology researchers and forward-thinking companies are experimenting with collaborative robots (aka cobots), powered by artificial intelligence (AI), to explore various automation scenarios as part of the digital transformation of the industry. Intelligent cobots are expected to be the dominant type of robots in the future of work in construction. However, the black-box nature of AI-powered cobots and unknown technical and psychological aspects of introducing them to job sites are precursors to trust challenges. By analyzing the results of semi-structured interviews with construction practitioners using grounded theory, this paper investigates the characteristics of trustworthy AI-powered cobots in construction. The study found that while the key trust factors identified in a systematic literature review -- conducted previously by the authors -- resonated with the field experts and end users, other factors such as financial considerations and the uncertainty associated with change were also significant barriers against trusting AI-powered cobots in construction.Comment: 2023 ASCE International Conference on Computing in Civil Engineering (I3CE

A 3D-printed microfluidic-enabled hollow microneedle architecture for transdermal drug delivery.

Embedding microfluidic architectures with microneedles enables fluid management capabilities that present new degrees of freedom for transdermal drug delivery. To this end, fabrication schemes that can simultaneously create and integrate complex millimeter/centimeter-long microfluidic structures and micrometer-scale microneedle features are necessary. Accordingly, three-dimensional (3D) printing techniques are suitable candidates because they allow the rapid realization of customizable yet intricate microfluidic and microneedle features. However, previously reported 3D-printing approaches utilized costly instrumentation that lacked the desired versatility to print both features in a single step and the throughput to render components within distinct length-scales. Here, for the first time in literature, we devise a fabrication scheme to create hollow microneedles interfaced with microfluidic structures in a single step. Our method utilizes stereolithography 3D-printing and pushes its boundaries (achieving print resolutions below the full width half maximum laser spot size resolution) to create complex architectures with lower cost and higher print speed and throughput than previously reported methods. To demonstrate a potential application, a microfluidic-enabled microneedle architecture was printed to render hydrodynamic mixing and transdermal drug delivery within a single device. The presented architectures can be adopted in future biomedical devices to facilitate new modes of operations for transdermal drug delivery applications such as combinational therapy for preclinical testing of biologic treatments

Carbon Nanotubes: Printed Carbon Nanotube Electronics and Sensor Systems (Adv. Mater. 22/2016).

Printed electronics and sensors enable new applications ranging from low-cost disposable analytical devices to large-area sensor networks. Recent progress in printed carbon nanotube electronics in terms of materials, processing, devices, and applications is discussed on page 4397 by A. Javey and co-workers. The research challenges and opportunities regarding the processing and system-level integration are also discussed for enabling of practical applications

Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform

Perspiration-based wearable biosensors facilitate continuous monitoring of individuals’ health states with real-time and molecular-level insight. The inherent inaccessibility of sweat in sedentary individuals in large volume (≥10 µL) for on-demand and in situ analysis has limited our ability to capitalize on this noninvasive and rich source of information. A wearable and miniaturized iontophoresis interface is an excellent solution to overcome this barrier. The iontophoresis process involves delivery of stimulating agonists to the sweat glands with the aid of an electrical current. The challenge remains in devising an iontophoresis interface that can extract sufficient amount of sweat for robust sensing, without electrode corrosion and burning/causing discomfort in subjects. Here, we overcame this challenge through realizing an electrochemically enhanced iontophoresis interface, integrated in a wearable sweat analysis platform. This interface can be programmed to induce sweat with various secretion profiles for real-time analysis, a capability which can be exploited to advance our knowledge of the sweat gland physiology and the secretion process. To demonstrate the clinical value of our platform, human subject studies were performed in the context of the cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation. With our platform, we detected the elevated sweat electrolyte content of cystic fibrosis patients compared with that of healthy control subjects. Furthermore, our results indicate that oral glucose consumption in the fasting state is followed by increased glucose levels in both sweat and blood. Our solution opens the possibility for a broad range of noninvasive diagnostic and general population health monitoring applications

Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis

Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual’s state of health. Sampling human sweat, which is rich in physiological information, could enable non-invasive monitoring. Previously reported sweat-based and other non-invasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications

Hydrogel‐Enabled Transfer‐Printing of Conducting Polymer Films for Soft Organic Bioelectronics

The use of conducting polymers such as poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) for the development of soft organic bioelectronic devices, such as organic electrochemical transistors (OECTs), is rapidly increasing. However, directly manipulating conducting polymer thin films on soft substrates remains challenging, which hinders the development of conformable organic bioelectronic devices. A facile transfer‐printing of conducting polymer thin films from conventional rigid substrates to flexible substrates offers an alternative solution. In this work, it is reported that PEDOT:PSS thin films on glass substrates, once mixed with surfactants, can be delaminated with hydrogels and thereafter be transferred to soft substrates without any further treatments. The proposed method allows easy, fast, and reliable transferring of patterned PEDOT:PSS thin films from glass substrates onto various soft substrates, facilitating their application in soft organic bioelectronics. By taking advantage of this method, skin‐attachable tattoo‐OECTs are demonstrated, relevant for conformable, imperceptible, and wearable organic biosensing.The use of hydrogels enables transfer‐printing of poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate thin films from glass substrates onto various soft substrates. Taking advantage of this technique, skin‐attachable organic electrochemical transistors (OECTs) are fabricated on commercially available tattoo paper. Wearable tattoo‐OECTs are further demonstrated with the integration of a wireless readout system.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154307/1/adfm201906016.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154307/2/adfm201906016_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154307/3/adfm201906016-sup-0001-SuppMat.pd

Investigation of Cortisol Dynamics in Human Sweat Using a Graphene-Based Wireless mHealth System

Prompt and accurate detection of stress is essential to the monitoring and management of mental health and human performance. Considering that current methods such as questionnaires are very subjective, we propose a highly sensitive, selective, miniaturized mHealth device based on laser-enabled flexible graphene sensor to non-invasively monitor the level of stress hormones (e.g., cortisol). We report a strong correlation between sweat and circulating cortisol and demonstrate the prompt determination of sweat cortisol variation in response to acute stress stimuli. Moreover, we demonstrate, for the first time, the diurnal cycle and stress-response profile of sweat cortisol, revealing the potential of dynamic stress monitoring enabled by this mHealth sensing system. We believe that this platform could contribute to fast, reliable, and decentralized healthcare vigilance at the metabolic level, thus providing an accurate snapshot of our physical, mental, and behavioral changes