5 research outputs found
Augmenting a Firefighters PPE -- Gas Mask SCBA
PPE (Personal Protective Equipment) has allowed firefighters to perform their
everyday tasks without getting harmed since the mid 1800s. Now, the advancement
of technology has given rise to the improvements of PPE. PPE can now include
sensors to detect any number of environmental hazards (chemical, biological,
temperature etc.). As the GT class of CS3750, we have decided to create a
version of an interface design sensor that will help firefighters in two ways:
navigation and communication. In order to augment a firefighter display when
they are within a building, we chose to augment their SCBA (self-contained
breathing apparatus). The gas mask will include a small screen that displays
vital information directly towards the firefighter without need of any other
support. We used the Google Glass to display vital information directly towards
the eye in a minimalistic manner, while also augmenting that by adding LED
lights to simulate someone calling their name or other auditory signals.While
our prototype focuses on two main components of a firefighters search and
rescue in a building, both of them combine to augment a firefighters display
when searching throughout a building to help improve accuracy, speed and
overall experience
A comprehensive comparative study on mid-term clinical and functional outcomes in Indian patients following bilateral total knee arthroplasty: assessing the impact of body mass index on post-total knee arthroplasty results
Background: Limited research exists on Indian obese patients undergoing simultaneous bilateral total knee arthroplasty (bTKA), necessitating a comprehensive and comparative analysis with non-obese counterparts. This study presents an observational and prospective assessment of Indian patients who underwent cruciate retaining/posterior stabilized (CR/PS) metal-backed implant surgeries from 2016 to 2019.
Methods: The study encompassed 190 patients (380 knees) undergoing bTKA, classified by World Health Organization (WHO) weight stratification: normal weight (cohort 1, n=51), overweight (cohort 2, n=85), and obese (cohort 3, n=54). Primary endpoints were implant survivorship and revision rates, with secondary endpoints including range of motion (ROM), knee society score (KSS), Western Ontario and McMaster Universities osteoarthritis index (WOMAC), and SF-36 scores.
Results: Female representation dominated all groups (88.24%, 87.06%, and 90.74%). End-stage osteoarthritis occurred in 94.12%, 96.47%, and 98.15%, respectively. Over the 3-year follow-up, four fatalities occurred, with 186 patients completing the study. ROM showed significant improvement after three years, with baseline values increasing from 93.29°±18.29° (cohort 1) to 123.97°±2.28°, 122.86°±5.03°, and 122.67°±4.77°, respectively (p<0.001). KSS demonstrated substantial improvement (cohort 1: 89.87±6.48, cohort 2: 90.47±8.40, cohort 3: 90.52±8.07) after three years. A 100% success rate and no revisions indicated implant durability. WOMAC and SF-36 questionnaires exhibited significant improvements in pain, stiffness, and overall well-being (p<0.001) after bTKA.
Conclusions: This mid-term CR/PS knee survival analysis underscores 100% implant functionality, improved knee function, and enhanced quality of life for all patients, irrespective of their body mass index (BMI). Simultaneous bilateral TKA with CR/PS implants demonstrates favourable outcomes, affirming its efficacy as a viable treatment option
Age wise comparative analysis of patients undergoing total knee arthroplasty: a multicenter indigenous experience
Background: This study assesses the mid-term clinical and functional outcomes, implant survivorship and impact of age on patients implanted with either cruciate retaining/posterior stabilized (CR/PS) total knee system (TKS).
Method: This is an ongoing, prospective, multicentre, real-world study enrolling 300 patients: younger adults (<55 years; n=69), older adults (55 years to <65 years; n=92) and elders (≥65 years; n=139). Primary safety endpoints: implant survivorship and cumulative revision rate. Secondary endpoints: Knee Society Score (KSS), Western Ontario and McMaster universities osteoarthritis (WOMAC) score, range of motion (ROM), SF-36 questionnaire for assessment of quality of life (QoL), radiographic analysis, and any adverse events at 6 weeks, 6 months, 1-3 years.Â
Results: Primary endpoint demonstrated absence of any revision across all age categories during the 3 years study period. Secondary outcomes KSS (clinical and functional) showed non-significant difference among elderly (91.13±7.90 and 98.18±4.62, respectively) in comparison to young adults (91.03±8.61 and 98.91±3.75, respectively). All three age-groups showed significant improvement in ROM (p<0.001) till 3 years 121.05°±7.74°, 123.22°±4.26°, and 122.43°±5.8° respectively, with no differences among the age groups. We observed that WOMAC and SF-36 QoL scores improved with each follow-up (p<0.001) across all age groups. Radiographs showed no implant wear or osteolysis during the investigation.
Conclusions: Age seems to play no notable role on the post-TKA outcomes. Over a 3-year period, we observed marked enhancements in patient measures such as ROM, KSS, WOMAC, and QoL indicating and strongly affirming the safety and efficacy of CR/PS TKS prostheses.
Visual Estimation of Fingertip Pressure on Diverse Surfaces using Easily Captured Data
People often use their hands to make contact with the world and apply
pressure. Machine perception of this important human activity could be widely
applied. Prior research has shown that deep models can estimate hand pressure
based on a single RGB image. Yet, evaluations have been limited to controlled
settings, since performance relies on training data with high-resolution
pressure measurements that are difficult to obtain. We present a novel approach
that enables diverse data to be captured with only an RGB camera and a
cooperative participant. Our key insight is that people can be prompted to
perform actions that correspond with categorical labels describing contact
pressure (contact labels), and that the resulting weakly labeled data can be
used to train models that perform well under varied conditions. We demonstrate
the effectiveness of our approach by training on a novel dataset with 51
participants making fingertip contact with instrumented and uninstrumented
objects. Our network, ContactLabelNet, dramatically outperforms prior work,
performs well under diverse conditions, and matched or exceeded the performance
of human annotators