Hand hygiene is crucial in preventing the spread of
infections and diseases. Lack of hand hygiene is one of the major
reasons for healthcare associated infections (HAIs) in hospitals.
Adherence to hand hygiene compliance by the workers in the food
business is very important for preventing food-borne illness. In
addition to healthcare settings and food businesses, hand washing
is also vital for personal well-being. Despite the importance of
hand hygiene, people often do not wash hands when necessary.
Automatic detection of hand washing activity can facilitate justin-time alerts when a person forgets to wash hands. Monitoring
hand washing practices is also essential in ensuring accountability
and providing personalized feedback, particularly in hospitals
and food businesses. Inertial sensors available in smart wrist
devices can capture hand movements, and so it is feasible to detect
hand washing using these devices. However, it is challenging to
detect hand washing using wrist wearable sensors since hand
movements are associated with a wide range of activities. In this
paper, we present HAWAD, a robust solution for hand washing
detection using wrist wearable inertial sensors. We leverage the
distribution of penultimate layer output of a neural network to
detect hand washing from a wide range of activities. Our method
reduces false positives by 77% and improves F1-score by 30%
compared to the baseline method.
more »
« less
Clean Vibes: Hand Washing Monitoring Using Structural Vibration Sensing
We present a passive and non-intrusive sensing system for monitoring hand washing activity using structural vibration sensing. Proper hand washing is one of the most effective ways to limit the spread and transmission of disease, and has been especially critical during the COVID-19 pandemic. Prior approaches include direct observation and sensing-based approaches, but are limited in non-clinical settings due to operational restrictions and privacy concerns in sensitive areas such as restrooms. Our work introduces a new sensing modality for hand washing monitoring, which measures hand washing activity-induced vibration responses of sink structures, and uses those responses to monitor the presence and duration of hand washing. Primary research challenges are that vibration responses are similar for different activities, occur on different surfaces/structures, and tend to overlap/coincide. We overcome these challenges by extracting information about signal periodicity for similar activities through cepstrum-based features, leveraging hierarchical learning to differentiate activities on different surfaces, and denoting “primary/secondary” activities based on their relative frequency and importance. We evaluate our approach using real-world hand washing data across 4 different sink structures/locations, and achieve an average F1-score for hand washing activities of 0.95, which represents a 8.8X and 10.2X reduction in error over two different baseline approaches.
more »
« less
- Award ID(s):
- 2026699
- NSF-PAR ID:
- 10333667
- Date Published:
- Journal Name:
- ACM Transactions on Computing for Healthcare
- ISSN:
- 2691-1957
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Loss of operation or devastating damage to buildings and industrial structures, as well as equipment housed in them, has been observed due to earthquake-induced vibrations. A common source of operational downtime is due to the performance reduction of vital equipment, which are sensitive to the total transmitted acceleration. A well-known method of protecting such equipment is seismic isolation of the equipment itself (or a group of equipment), as opposed to the entire structure due to the lower cost of implementation. The first objective of this dissertation is assessing a rolling isolation system (RIS) based on existing design guidelines for telecommunications equipment. A discrepancy is observed between the required response spectrum (RRS) and the one and only accelerogram recommended in the guideline. Several filters are developed to generate synthetic accelerograms that are compatible with the RRS. The generated accelerograms are used for probabilistic assessment of a RIS that is acceptable per the guideline. This assessment reveals large failure probability due to displacement demands in excess of the displacement capacity of the RIS. When the displacement demands on an isolation system are in excess of its capacity, impacts result in spikes in transmitted acceleration. Therefore, the second objective of this dissertation is to design impact prevention/mitigation mechanisms. A dual-mode system is proposed where the behavior changes when the displacement exceeds a predefined threshold. A new piecewise optimal control approach is developed and applied to find the best possible mechanism for the region beyond the threshold. By utilizing the designed curves obtained from the proposed optimal control procedure, a Kelvin-Voigt device is tuned for illustrative purposes. On the other hand, the preference for protecting equipment decreases as the earthquake intensity increases. In extreme seismic loading, the response mitigation of the primary structure (i.e., life safety and collapse prevention) is of greater concern than protecting isolated equipment. Therefore, the third objective of this dissertation is to develop an innovative dual-mode system that can behave as equipment isolation under low to moderate seismic loading and passively transition to behave as a vibration absorber for the primary structure under extreme seismic loading. To reduce the computational cost of simulating a large linear elastic structure with nonlinear attachments (i.e., equipment isolation with cubic hardening nonlinearity), a reduced order modeling method is introduced that can capture the behavior of such nonlinear coupled systems. The method is applied to study the feasibility of dual-mode vibration isolation/absorber. To this end, nonlinear transmissibility curves for the roof displacement and isolated mass total acceleration are developed from the steady-state responses of dual-mode systems using the harmonic balanced method. The final objective of this dissertation is to extend the reduced order modeling method developed for linear elastic structure with nonlinear attachment to inelastic structures (without attachments). The new inelastic model condensation (IMC) method uses the modal properties of the full structural model (in the elastic range) to construct a linear reduced order model in conjunction with a hysteresis model to capture the hysteretic inter-story restoring forces. The parameters of these hysteretic forces are easily tuned, in order to fit the inelastic behavior of the condensed structure to that of the full model under a variety of simple loading scenarios. The fidelity of structural models condensed in this way is demonstrated via simulation for different ground motion intensities on three different building structures with various heights. The simplicity, accuracy, and efficiency of this approach could significantly alleviate the computational burden of performance-based earthquake engineering.more » « less
-
more » « less
Abstract Real-time, low-cost, and wireless mechanical vibration monitoring is necessary for industrial applications to track the operation status of equipment, environmental applications to proactively predict natural disasters, as well as day-to-day applications such as vital sign monitoring. Despite this urgent need, existing solutions, such as laser vibrometers, commercial Wi-Fi devices, and cameras, lack wide practical deployment due to their limited sensitivity and functionality. Here we proposed a fully passive, metamaterial-based vibration processing device, fabricated prototypes working at different frequencies ranging from 5 Hz to 285 Hz, and verified that the device can improve the sensitivity of wireless vibration measurement methods by more than ten times when attached to vibrating surfaces. Additionally, the device realizes an analog real-time vibration filtering/labeling effect, and the device also provides a platform for surface editing, which adds more functionalities to the current non-contact sensing systems. Finally, the working frequency of the device is widely adjustable over orders of magnitudes, broadening its applicability to different applications, such as structural health diagnosis, disaster warning, and vital signal monitoring.
-
more » « less
Abstract Drylands are key contributors to interannual variation in the terrestrial carbon sink, which has been attributed primarily to broad‐scale climatic anomalies that disproportionately affect net primary production (NPP) in these ecosystems. Current knowledge around the patterns and controls of NPP is based largely on measurements of aboveground net primary production (ANPP), particularly in the context of altered precipitation regimes. Limited evidence suggests belowground net primary production (BNPP), a major input to the terrestrial carbon pool, may respond differently than ANPP to precipitation, as well as other drivers of environmental change, such as nitrogen deposition and fire. Yet long‐term measurements of BNPP are rare, contributing to uncertainty in carbon cycle assessments. Here, we used 16 years of annual NPP measurements to investigate responses of ANPP and BNPP to several environmental change drivers across a grassland–shrubland transition zone in the northern Chihuahuan Desert. ANPP was positively correlated with annual precipitation across this landscape; however, this relationship was weaker within sites. BNPP, on the other hand, was weakly correlated with precipitation only in Chihuahuan Desert shrubland. Although NPP generally exhibited similar trends among sites, temporal correlations between ANPP and BNPP within sites were weak. We found chronic nitrogen enrichment stimulated ANPP, whereas a one‐time prescribed burn reduced ANPP for nearly a decade. Surprisingly, BNPP was largely unaffected by these factors. Together, our results suggest that BNPP is driven by a different set of controls than ANPP. Furthermore, our findings imply belowground production cannot be inferred from aboveground measurements in dryland ecosystems. Improving understanding around the patterns and controls of dryland NPP at interannual to decadal scales is fundamentally important because of their measurable impact on the global carbon cycle. This study underscores the need for more long‐term measurements of BNPP to improve assessments of the terrestrial carbon sink, particularly in the context of ongoing environmental change.
-
The landscapes of many elementary, middle, and high school math classrooms have undergone major transformations over the last half-century, moving from drill-and-skill work to more conceptual reasoning and hands-on manipulative work. However, if you look at a college level calculus class you are likely to find the main difference is the professor now has a whiteboard marker in hand rather than a piece of chalk. It is possible that some student work may be done on the computer, but much of it contains the same type of repetitive skill building problems. This should seem strange given the advancements in technology that allow more freedom than ever to build connections between different representations of a concept. Several class activities have been developed using a combination of approaches, depending on the topic. Topics covered in the activities include Riemann Sums, Accumulation, Center of Mass, Volumes of Revolution (Discs, Washers, and Shells), and Volumes of Similar Cross-section. All activities use student note outlines that are either done in a whole group interactive-lecture approach, or in a group work inquiry-based approach. Some of the activities use interactive graphs designed on desmos.com and others use physical models that have been designed in OpenSCAD and 3D-printed for students to use in class. Tactile objects were developed because they should provide an advantage to students by enabling them to physically interact with the concepts being taught, deepening their involvement with the material, and providing more stimuli for the brain to encode the learning experience. Web-based activities were developed because the topics involved needed substantial changes in graphical representations (i.e. limits with Riemann Sums). Assessment techniques for each topic include online homework, exams, and online concept questions with an explanation response area. These concept questions are intended to measure students’ ability to use multiple representations in order to answer the question, and are not generally computational in nature. Students are also given surveys to rate the overall activities as well as finer grained survey questions to try and elicit student thoughts on certain aspects of the models, websites, and activity sheets. We will report on student responses to the activity surveys, looking for common themes in students’ thoughts toward specific attributes of the activities. We will also compare relevant exam question responses and online concept question results, including common themes present or absent in student reasoning.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3511890
