A multi-sensor wearable system for the assessment of diseased gait in real-world conditions.

Introduction: Accurately assessing people's gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors). Methods: The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-h of real-world unsupervised activity. Results and discussion: Excellent absolute agreement (ICC >0.95) and very limited mean absolute errors were observed for all cohorts and digital mobility outcomes (cadence ≤0.61 steps/min, stride length ≤0.02 m, walking speed ≤0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the daily-life simulation (cadence 2.72-4.87 steps/min, stride length 0.04-0.06 m, walking speed 0.03-0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-h acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

An assessment of heavy metals in green sea turtle (Chelonia mydas) hatchlings from Saudi Arabia's largest rookery, Ras Baridi.

Background: Anthropogenic sources can lead to the accumulation of heavy metals in marine organisms through ingestion, absorption, or inhalation. For sea turtle embryos, heavy metals can be absorbed into the egg from the incubation environment or be maternally transferred to the offspring causing neurological, reproductive, and developmental problems. Here, we report heavy metal concentrations in green turtle hatchlings from the largest rookery on the Red Sea, Ras Baridi. Methods: Deceased hatchlings were collected from two beaches near a cement factory at Ras Baridi, from which heavy metal concentrations (chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), cadmium (Cd), and lead (Pb)) were measured from the liver, muscle, and residual yolk of the hatchlings. Results: Although based on a small sample of hatchlings, the data presented here provides the first measurements of heavy metals from sea turtles in the Red Sea and highlights the link between human activity and its impact on the ecology of sea turtles. In general, the heavy metal concentrations of heavy metals were not significantly different between the beach next to the cement factory and the beach downwind from the factory. However, the concentrations of heavy metals were significantly different between sampled tissues (liver, muscle, and residual yolk). Discussion: This study provides insight into current heavy metal levels in green turtle hatchlings, which can be used as bio-indicators for environmental contaminants as coastal development increases in the Red Sea. Moreover, we found a lack of standardized methodology to evaluate heavy metals in hatchling sea turtles. Future efforts should work toward creating comparable techniques for long-term heavy metal monitoring, as this is a useful determinant of anthropogenic pollution.

An Objective Methodology for the Selection of a Device for Continuous Mobility Assessment.

Continuous monitoring by wearable technology is ideal for quantifying mobility outcomes in "real-world" conditions. Concurrent factors such as validity, usability, and acceptability of such technology need to be accounted for when choosing a monitoring device. This study proposes a bespoke methodology focused on defining a decision matrix to allow for effective decision making. A weighting system based on responses (n = 69) from a purpose-built questionnaire circulated within the IMI Mobilise-D consortium and its external collaborators was established, accounting for respondents' background and level of expertise in using wearables in clinical practice. Four domains (concurrent validity, CV; human factors, HF; wearability and usability, WU; and data capture process, CP), associated evaluation criteria, and scores were established through literature research and group discussions. While the CV was perceived as the most relevant domain (37%), the others were also considered highly relevant (WU: 30%, HF: 17%, CP: 16%). Respondents (~90%) preferred a hidden fixation and identified the lower back as an ideal sensor location for mobility outcomes. Overall, this study provides a novel, holistic, objective, as well as a standardized approach accounting for complementary aspects that should be considered by professionals and researchers when selecting a solution for continuous mobility monitoring.