Wearables and Internet of Things (IoT) Technologies for Fitness Assessment: A Systematic Review

A feedback-driven brain organoid platform enables automated maintenance and high-resolution neural activity monitoring

The analysis of tissue cultures, particularly brain organoids, requires a sophisticated integration and coordination of multiple technologies for monitoring and measuring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Our approach enables continuous, communicative, non-invasive interactions within an Internet of Things (IoT) architecture among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids while measuring their neuronal activity. The organoids are cultured in custom, 3D-printed chambers affixed to commercial microelectrode arrays. Periodic feeding is achieved using programmable microfluidic pumps. We developed a computer vision fluid volume estimator used as feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a set of 7-day studies of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated protocols were validated in maintaining robust neural activity throughout the experiment. The automated system enabled hourly electrophysiology recordings for the 7-day studies. Median neural unit firing rates increased for every sample and dynamic patterns of organoid firing rates were revealed by high-frequency recordings. Surprisingly, feeding did not affect firing rate. Furthermore, performing media exchange during a recording showed no acute effects on firing rate, enabling the use of this automated platform for reagent screening studies.

Combined Self-Reported and Device-Measured Physical Activity Assessment and Disability Incidence in Older Adults

OBJECTIVES

To clarify the relationship between self-reported and device-measured physical activity (PA) and disability incidences in community-dwelling older adults.

DESIGN

Prospective cohort study.

SETTING AND PARTICIPANTS

In total, 4504 (median age 75 [range, 72-79] years; women, 52.1%) community-dwelling older adults were included in this study.

METHODS

Device-measured moderate-to-vigorous PA (MVPA) was measured using a triaxial accelerometer. Self-reported MVPA was assessed using the Japanese version of the International Physical Activity Questionnaire, Short Form. The cutoff MVPA was 150 min/wk. PA was divided into 4 groups based on self-reported and device-measured assessments: (1) self-reported/device-measured inactive, (2) self-reported active/device-measured inactive, (3) self-reported inactive/device-measured active, and (4) self-reported/device-measured active. The disability incidence, defined as a long-term care insurance certification of any level indicating a requirement for support or continuous care, was prospectively determined using data extracted from the Japanese long-term care insurance system.

RESULTS

Of the participants, 892 (19.8%) developed disabilities within 62 (range, 60-64) months. The prevalence of self-reported inactive/device-measured inactive, self-reported active/device-measured inactive, self-reported inactive/device-measured active, and self-reported active/device-measured active were 884 (34.9%), 441 (17.4%), 693 (27.3%), and 515 (20.3%) participants, respectively. Multivariate Cox regression analysis showed that self-reported/device-measured active, self-reported inactive/device-measured active, and self-reported active/device-measured inactive independently decreased the disability incidence risk (self-reported/device-measured active: hazard ratio [HR], 0.555, 95% confidence interval [CI], 0.412-0.749; self-report inactive/device-measured active: HR, 0.656; 95% CI, 0.518-0.831; self-reported active/device-measured inactive: HR, 0.718; 95% CI, 0.556-0.928). In the post hoc analysis, those who were self-reported active/device-measured inactive were divided into 2 groups according to involvement in sports. Those who played sports had a lower disability risk; however, the difference was not significant.

CONCLUSIONS AND IMPLICATIONS

Combined self-reported and device-measured PA assessments may allow for disability risk stratification in older adults. The findings will also help in creating methods for evaluating PA levels to prevent disability incidences among older adults.

Electrochemical sensing at the fingertips: Wearable glove-based sensors for detection of 4-nitrophenol, picric acid and diazepam

A wearable glove-based sensor is a portable and practical approach for onsite detection/monitoring of a variety of chemical threats. Herein, we report a flexible and sensitive wearable sensor fabricated on the nitrile glove fingertips by stencil-printing technique. The working electrodes were modified with multiwalled carbon nanotubes (MWCNTs)/poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) for sensitive and real-time analyses of hazardous or chemical treats, as picric acid (PA) explosive, diazepam (DZ) as drug-facilitated crimes and the emerging pollutant 4-nitrophenol (4-NP). The multi-sensing platform towards PA, 4-NP, and DZ offers the ability of in-situ qualitative and quantitative analyses of powder and liquid samples. A simple sampling by touching or swiping the fingertip sensor on the sample or surface under investigation using an ionic hydrogel combined with fast voltammetry measurement provides timely point-of-need analyses. The wearable glove-based sensor uses the square wave voltammetry (SWV) technique and exhibited excellent performance to detect PA, 4-NP, and DZ, resulting in limits of detection (LOD) of 0.24 μM, 0.35 μM, 0.06 μM, respectively, in a wide concentration range (from 0.5 μM to 100 μM). Also, we obtained excellent manufacturing reproducibility with relative standard deviations (RSD) in the range of 3.65%-4.61% using 7 different wearable devices (n = 7) and stability in the range of 4.86%-6.61% using different electrodes stored for 10 days at room temperature (n = 10), demonstrating the excellent sensor-to-sensor reproducibility and stability for reliable in-field measurements. The stretchable sensor presented great mechanical robustness, supporting up to 80 bending or stretching deformation cycles without significant voltammetric changes. Collectively, our wearable glove-based sensor may be employed for analyses of chemical contaminants of concern, such as explosives (PA), drugs (DZ), and emerging pollutants (4-NP), helping in environmental and public safety control.

Enhancing Tennis Practice: Sensor Fusion and Pose Estimation with a Smart Tennis Ball

This article demonstrates the integration of sensor fusion for pose estimation and data collection in tennis balls, aiming to create a smaller, less intrusive form factor for use in progressive learning during tennis practice. The study outlines the design and implementation of the Bosch BNO055 smart sensor, which features built-in managed sensor fusion capabilities. The article also discusses deriving additional data using various mathematical and simulation methods to present relevant orientation information from the sensor in Unity. Embedded within a Vermont practice foam tennis ball, the final prototype product communicates with Unity on a laptop via Bluetooth. The Unity interface effectively visualizes the ball's rotation, the resultant acceleration direction, rotations per minute (RPM), and the orientation relative to gravity. The system successfully demonstrates accurate RPM measurement, provides real-time visualization of ball spin and offers a pathway for innovative applications in tennis training technology.

Running Economy in the Vertical Kilometer

New and promising variables are being developed to analyze performance and fatigue in trail running, such as mechanical power, metabolic power, metabolic cost of transport and mechanical efficiency. The aim of this study was to analyze the behavior of these variables during a real vertical kilometer field test. Fifteen trained trail runners, eleven men (from 22 to 38 years old) and four women (from 19 to 35 years old) performed a vertical kilometer with a length of 4.64 km and 835 m positive slope. During the entire race, the runners were equipped with portable gas analyzers (Cosmed K5) to assess their cardiorespiratory and metabolic responses breath by breath. Significant differences were found between top-level runners versus low-level runners in the mean values of the variables of mechanical power, metabolic power and velocity. A repeated-measures ANOVA showed significant differences between the sections, the incline and the interactions between all the analyzed variables, in addition to differences depending on the level of the runner. The variable of mechanical power can be statistically significantly predicted from metabolic power and vertical net metabolic COT. An algebraic expression was obtained to calculate the value of metabolic power. Integrating the variables of mechanical power, vertical velocity and metabolic power into phone apps and smartwatches is a new opportunity to improve performance monitoring in trail running.

The molecular athlete: exercise physiology from mechanisms to medals

Human skeletal muscle demonstrates remarkable plasticity, adapting to numerous external stimuli including the habitual level of contractile loading. Accordingly, muscle function and exercise capacity encompass a broad spectrum, from inactive individuals with low levels of endurance and strength to elite athletes who produce prodigious performances underpinned by pleiotropic training-induced muscular adaptations. Our current understanding of the signal integration, interpretation, and output coordination of the cellular and molecular mechanisms that govern muscle plasticity across this continuum is incomplete. As such, training methods and their application to elite athletes largely rely on a "trial-and-error" approach, with the experience and practices of successful coaches and athletes often providing the bases for "post hoc" scientific enquiry and research. This review provides a synopsis of the morphological and functional changes along with the molecular mechanisms underlying exercise adaptation to endurance- and resistance-based training. These traits are placed in the context of innate genetic and interindividual differences in exercise capacity and performance, with special consideration given to aging athletes. Collectively, we provide a comprehensive overview of skeletal muscle plasticity in response to different modes of exercise and how such adaptations translate from "molecules to medals."

ehealth technology in cardiac exercise therapeutics for pediatric patients with congenital and acquired heart conditions: a summary of evidence and future directions

Many children and adolescents with congenital and acquired heart disease (CHD) are physically inactive and participate in an insufficient amount of moderate-to-vigorous intensity exercise. Although physical activity (PA) and exercise interventions are effective at improving short- and long-term physiological and psychosocial outcomes in youth with CHD, several barriers including resource limitations, financial costs, and knowledge inhibit widespread implementation and dissemination of these beneficial programs. New and developing eHealth, mHealth, and remote monitoring technologies offer a potentially transformative and cost-effective solution to increase access to PA and exercise programs for youth with CHD, yet little has been written on this topic. In this review, a cardiac exercise therapeutics (CET) model is presented as a systematic approach to PA and exercise, with assessment and testing guiding three sequential PA and exercise intervention approaches of progressive intensity and resource requirements: (1) PA and exercise promotion within a clinical setting; (2) unsupervised exercise prescription; and (3) medically supervised fitness training intervention (i.e., cardiac rehabilitation). Using the CET model, the goal of this review is to summarize the current evidence describing the application of novel technologies within CET in populations of children and adolescents with CHD and introduce potential future applications of these technologies with an emphasis on improving equity and access to patients in low-resource settings and underserved communities.

Force plate vertical jump scans are not a valid proxy for physical fitness in US special warfare trainees

Background: The United States Air Force Special Warfare Training Wing (SWTW) administers a comprehensive physical fitness test to active duty Airmen entering the Special Warfare training pipeline. The Sparta Science™ system utilizes proprietary software to analyze the force-time curve of a vertical jump and purports to serve as a proxy for traditional military fitness tests. The Sparta Science™ system produces four proprietary metrics, including the Sparta™ Score, which is correlated to high magnitudes of force production purportedly performance. This study investigated how Sparta™ Jump Scans correlate to components of a physical fitness test utilized within the SW training pipeline. Methods: At the entry and exit of an 8-week Special Warfare Training Wing preparatory course (SW PREP), 643 trainees completed both an initial and final Sparta™ Jump Scan and a Candidate Fitness Test (CFT). The Candidate Fitness Test consists of eight components and tests several different domains of fitness including strength, power, muscular endurance, swimming proficiency, and cardiovascular fitness. Paired t-tests were used to determine if Sparta™ Jump Scan metrics and CFT components changed during SW PREP. Sparta™ Score's correlation was assessed against every other Sparta™ Jump Scan metric and all CFT fitness measures. Results: This study found that the Sparta™ Jump Scan metrics decline slightly over SW PREP (p < 0.05; negligible-small effect size), while most CFT measures improve (p < 0.05; small-medium effect size). Changes in Sparta™ Jump Scan metrics did not reflect the changes in CFT performance over SW PREP (r ²: 0.00-0.03). Conclusion: The Sparta™ Score was not correlated to the most tactically-relevant fitness measures (rucking and swimming), and only weakly correlated with the only jumping measure on the fitness test, the standing broad jump.