Things Are Changing so Fast: Integrative Technology for Preserving Cognitive Health and Community History.

Background and Objectives: Multimodal interventions are increasingly targeting multiple cognitive decline risk factors. However, technology remains mostly adjunctive, largely prioritizes age relevancy over cultural relevancy, and often targets individual health without lasting, community-wide deliverables. Meanwhile, African Americans remain overburdened by cognitive risk factors yet underrepresented in cognitive health and technology studies. The Sharing History through Active Reminiscence and Photo-imagery (SHARP) program increases physical, social, and cognitive activity within a culturally meaningful context that produces community deliverables-an oral history archive and cognitive health education. Design and Methods: The SHARP application was tested with 19 African Americans ≥55 years, aiming for an easy, integrative, and culturally meaningful experience. The application guided triads in walks 3 times weekly for 6 months in Portland, Oregon's historically Black neighborhoods; local historical images prompted recorded conversational reminiscence. Focus groups evaluated factors influencing technology acceptance-attitudes about technology, usefulness, usability, and relevance to integrating program goals. Thematic analysis guided qualitative interpretation. Results: Technology acceptance was influenced by group learning, paper-copy replicas for reluctant users, ease of navigation, usefulness for integrating and engaging in health behaviors, relevance to integrating individual benefit and the community priority of preserving history amidst gentrification, and flexibility in how the community uses deliverables. Perceived community benefits sustained acceptance despite intermittent technology failure. Discussion and Implications: We offer applicable considerations for brain health technology design, implementation, and deliverables that integrate modalities, age, and cultural relevance, and individual and community benefit for more meaningful, and thus more motivated community engagement.

Knee Ligament Injury and the Clinical Application of Tissue Engineering Techniques: A Systematic Review.

BACKGROUND: The incidence of knee ligament injury is increasing and represents a significant cost to healthcare providers. Current interventions include tissue grafts, suture repair and non-surgical management. These techniques have demonstrated good patient outcomes but have been associated graft rejection, infection, long term immobilization and reduced joint function. The limitations of traditional management strategies have prompted research into tissue engineering of knee ligaments. OBJECTIVE: This paper aims to evaluate whether tissue engineering of knee ligaments offers a viable alternative in the clinical management of knee ligament injuries. A search of existing literature was performed using OVID Medline, Embase, AMED, PubMed and Google Scholar, and a manual review of citations identified within these papers. RESULTS: Silk, polymer and extracellular matrix based scaffolds can all improve graft healing and collagen production. Fibroblasts and stem cells demonstrate compatibility with scaffolds, and have been shown to increase organized collagen production. These effects can be augmented using growth factors and extracellular matrix derivatives. Animal studies have shown tissue engineered ligaments can provide the biomechanical characteristics required for effective treatment of knee ligament injuries. CONCLUSION: There is a growing clinical demand for a tissue engineered alternative to traditional management strategies. Currently, there is limited consensus regarding material selection for use in tissue engineered ligaments. Further research is required to optimize tissue engineered ligament production before clinical application. Controlled clinical trials comparing the use of tissue engineered ligaments and traditional management in patients with knee ligament injury could determine whether they can provide a cost-effective alternative.

A time-frequency respiration tracking system using non-contact bed sensors with harmonic artifact rejection.

Sleep apnea is a breathing disorder that affects many individuals and has been associated with serious health conditions such as cardiovascular disease. Clinical diagnosis of sleep apnea requires that a patient spend the night in a sleep clinic while being wired up to numerous obtrusive sensors. We are developing a system that utilizes respiration rate and breathing amplitude inferred from non-contact bed sensors (i.e. load cells placed under bed supports) to detect sleep apnea. Multi-harmonic artifacts generated either biologically or as a result of the impulse response of the bed have made it challenging to track respiration rate and amplitude with high resolution in time. In this paper, we present an algorithm that can accurately track respiration on a second-by-second basis while removing noise harmonics. The algorithm is tested using data collected from 5 patients during overnight sleep studies. Respiration rate is compared with polysomnography estimations of respiration rate estimated by a technician following clinical standards. Results indicate that certain subjects exhibit a large harmonic component of their breathing signal that can be removed by our algorithm. When compared with technician transcribed respiration rates using polysomnography signals, we demonstrate improved accuracy of respiration rate tracking using harmonic artifact rejection (mean error: 0.18 breaths/minute) over tracking not using harmonic artifact rejection (mean error: -2.74 breaths/minute).