Detecting gunshots using wearable accelerometers.
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ABSTRACT:
SUBMITTER: Loeffler CE
PROVIDER: S-EPMC4153670 | biostudies-other | 2014
REPOSITORIES: biostudies-other
Publications
Gun violence continues to be a staggering and seemingly intractable issue in many communities. The prevalence of gun violence among the sub-population of individuals under court-ordered community supervision provides an opportunity for intervention using remote monitoring technology. Existing monitoring systems rely heavily on location-based monitoring methods, which have incomplete geographic coverage and do not provide information on illegal firearm use. This paper presents the first results d ...[more]
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Project description:BackgroundObstructive sleep apnea (OSA) is the most prevalent respiratory sleep disorder occurring in 9% to 38% of the general population. About 90% of patients with suspected OSA remain undiagnosed due to the lack of sleep laboratories or specialists and the high cost of gold-standard in-lab polysomnography diagnosis, leading to a decreased quality of life and increased health care burden in cardio- and cerebrovascular diseases. Wearable sleep trackers like smartwatches and armbands are booming, creating a hope for cost-efficient at-home OSA diagnosis and assessment of treatment (eg, continuous positive airway pressure [CPAP] therapy) effectiveness. However, such wearables are currently still not available and cannot be used to detect sleep hypopnea. Sleep hypopnea is defined by ≥30% drop in breathing and an at least 3% drop in peripheral capillary oxygen saturation (Spo2) measured at the fingertip. Whether the conventional measures of oxygen desaturation (OD) at the fingertip and at the arm or wrist are identical is essentially unknown.ObjectiveWe aimed to compare event-by-event arm OD (arm_OD) with fingertip OD (finger_OD) in sleep hypopneas during both naïve sleep and CPAP therapy.MethodsThirty patients with OSA underwent an incremental, stepwise CPAP titration protocol during all-night in-lab video-polysomnography monitoring (ie, 1-h baseline sleep without CPAP followed by stepwise increments of 1 cmH2O pressure per hour starting from 5 to 8 cmH2O depending on the individual). Arm_OD of the left biceps muscle and finger_OD of the left index fingertip in sleep hypopneas were simultaneously measured by frequency-domain near-infrared spectroscopy and video-polysomnography photoplethysmography, respectively. Bland-Altman plots were used to illustrate the agreements between arm_OD and finger_OD during baseline sleep and under CPAP. We used t tests to determine whether these measurements significantly differed.ResultsIn total, 534 obstructive apneas and 2185 hypopneas were recorded. Of the 2185 hypopneas, 668 (30.57%) were collected during baseline sleep and 1517 (69.43%), during CPAP sleep. The mean difference between finger_OD and arm_OD was 2.86% (95% CI 2.67%-3.06%, t667=28.28; P<.001; 95% limits of agreement [LoA] -2.27%, 8.00%) during baseline sleep and 1.83% (95% CI 1.72%-1.94%, t1516=31.99; P<.001; 95% LoA -2.54%, 6.19%) during CPAP. Using the standard criterion of 3% saturation drop, arm_OD only recognized 16.32% (109/668) and 14.90% (226/1517) of hypopneas at baseline and during CPAP, respectively.Conclusionsarm_OD is 2% to 3% lower than standard finger_OD in sleep hypopnea, probably because the measured arm_OD originates physiologically from arterioles, venules, and capillaries; thus, the venous blood adversely affects its value. Our findings demonstrate that the standard criterion of ≥3% OD drop at the arm or wrist is not suitable to define hypopnea because it could provide large false-negative results in diagnosing OSA and assessing CPAP treatment effectiveness.
| S-EPMC8367170 | biostudies-literature
Project description:BackgroundSubclinical (ie, threshold) social anxiety can greatly affect young people's lives, but existing solutions appear inadequate considering its rising prevalence. Wearable sensors may provide a novel way to detect social anxiety and result in new opportunities for monitoring and treatment, which would be greatly beneficial for persons with social anxiety, society, and health care services. Nevertheless, indicators such as skin temperature measured by wrist-worn sensors have not been used in prior work on physiological social anxiety detection.ObjectiveThis study aimed to investigate whether subclinical social anxiety in young adults can be detected using physiological data obtained from wearable sensors, including heart rate, skin temperature, and electrodermal activity (EDA).MethodsYoung adults (N=12) with self-reported subclinical social anxiety (measured using the widely used self-reported version of the Liebowitz Social Anxiety Scale) participated in an impromptu speech task. Physiological data were collected using an E4 Empatica wearable device. Using the preprocessed data and following a supervised machine learning approach, various classification algorithms such as Support Vector Machine, Decision Tree, Random Forest, and K-Nearest Neighbours (KNN) were used to develop models for 3 different contexts. Models were trained to differentiate (1) between baseline and socially anxious states, (2) among baseline, anticipation anxiety, and reactive anxiety states, and (3) social anxiety among individuals with social anxiety of differing severity. The predictive capability of the singular modalities was also explored in each of the 3 supervised learning experiments. The generalizability of the developed models was evaluated using 10-fold cross-validation as a performance index.ResultsWith modalities combined, the developed models yielded accuracies between 97.54% and 99.48% when differentiating between baseline and socially anxious states. Models trained to differentiate among baseline, anticipation anxiety, and reactive anxiety states yielded accuracies between 95.18% and 98.10%. Furthermore, the models developed to differentiate between social anxiety experienced by individuals with anxiety of differing severity scores successfully classified with accuracies between 98.86% and 99.52%. Surprisingly, EDA was identified as the most effective singular modality when differentiating between baseline and social anxiety states, whereas ST was the most effective modality when differentiating anxiety among individuals with social anxiety of differing severity.ConclusionsThe results indicate that it is possible to accurately detect social anxiety as well as distinguish between levels of severity in young adults by leveraging physiological data collected from wearable sensors.
| S-EPMC8532020 | biostudies-literature
Project description:The detection of significant moments can support the care of individuals with dementia by making visible what is most meaningful to them and maintaining a sense of interpersonal connection. We present a novel intelligent assistive technology (IAT) for the detection of significant moments based on patterns of physiological signal changes in individuals with dementia and their caregivers. The parameters of the IAT are tailored to each individual's idiosyncratic physiological response patterns through an iterative process of incorporating subjective feedback on videos extracted from candidate significant moments identified through the IAT algorithm. The IAT was tested on three dyads (individual with dementia and their primary caregiver) during an eight-week movement program. Upon completion of the program, the IAT identified distinct, personal characteristics of physiological responsiveness in each participant. Tailored algorithms could detect moments of significance experienced by either member of the dyad with an agreement with subjective reports of 70%. These moments were constituted by both physical and emotional significances (e.g., experiences of pain or anxiety) and interpersonal significance (e.g., moments of heighted connection). We provide a freely available MATLAB toolbox with the IAT software in hopes that the assistive technology community can benefit from and contribute to these tools for understanding the subjective experiences of individuals with dementia.
| S-EPMC6778872 | biostudies-literature
Project description:Light fidelity (LiFi), which is emerging as a compelling technology paradigm shifting the common means of high-capacity wireless communication technologies, requires wearable and full-duplex compact design because of its great significance in smart wearables as well as the 'Internet of Things'. However, the construction of the key component of wearable full-duplex LiFi, light-emitting/detecting bifunctional fibres, is still challenging because of the conflicting process between carrier separation and recombination, as well as the highly dynamic film-forming process. Here, we demonstrate light-emitting/detecting bifunctional fibres enabled by perovskite QDs with hybrid components. The hybrid perovskite inks endow fibres with super-smooth QD films. This, combined with the small exciton binding energy and high carrier mobility of perovskite QDs, enables successful integration of electroluminescence and photodetection into monofilaments. The bifunctional fibres possess the narrowest electroluminescence full width at half maximum of ~19 nm and, more importantly, the capability for simultaneously transmitting and receiving information. The successful fabrication of narrow emission full-duplex LiFi fibres paves the way for the fabrication and integration of low crosstalk interoperable smart wearables.
| S-EPMC7494868 | biostudies-literature
Project description:Ambulatory blood pressure (ABP) and home blood pressure (HBP) monitoring is currently recommended for management of hypertension. Nonetheless, traditional HBP protocols could overlook diurnal fluctuations, which could also be linked with adverse cardiovascular outcomes. In this observational study, we studied among a group of treated hypertensive patients (N = 62, age: 52.4 ± 10.4 years) by using out-of-office ABP and wearable HBP. They received one session of 24-h ABP measurement with an oscillometric upper-arm monitor, and totally three sessions of 7-day/6-time-daily wearable HBP measurement separated in each month with HeartGuide. Controlled hypertension is defined as an average BP <130/80 mmHg for both daytime ABP and HBP. There was substantial reliability (intraclass correlation coefficient, ICC 0.883-0.911) and good reproducibility (Cohen's kappa = 0.600) for wearable HBP measurement, especially before breakfast and after dinner. Among all patients, 27.4% had both uncontrolled HBP and ABP, 30.6% had uncontrolled HBP only, while 6.5% had uncontrolled ABP only. Female gender and increased numbers of anti-hypertensive agents are correlated with controlled hypertension. Patients with uncontrolled hypertension had a significantly higher maximal daytime blood pressure, which was previously signified as an imperial marker for cardiovascular risk. In conclusion, wearable HBP monitoring in accordance with a dedicated daily-living schedule results in good reliability and reproducibility. Patients with an uncontrolled wearable HBP should benefit from repeated HBP or ABP measurement for risk stratification.
| S-EPMC10994837 | biostudies-literature
Project description:Single-cell RNA sequencing of mouse amygdala using Drop-Seq
2017-10-11 | GSE103976 | GEO
Project description:ObjectiveTo evaluate the ability of a binocular automated pupillograph to discriminate healthy subjects from those with glaucoma.DesignCross-sectional observational study.ParticipantsBoth eyes of 116 subjects, including 66 patients with glaucoma in at least 1 eye and 50 healthy subjects from the Diagnostic Innovations in Glaucoma Study. Eyes were classified as glaucomatous by repeatable abnormal standard automated perimetry (SAP) or progressive glaucomatous changes on stereophotographs.MethodsAll subjects underwent automated pupillography using the RAPDx pupillograph (Konan Medical USA, Inc., Irvine, CA).Main outcome measuresReceiver operating characteristic (ROC) curves were constructed to assess the diagnostic ability of pupil response parameters to white, red, green, yellow, and blue full-field and regional stimuli. A ROC regression model was used to investigate the influence of disease severity and asymmetry on diagnostic ability.ResultsThe largest area under the ROC curve (AUC) for any single parameter was 0.75. Disease asymmetry (P <0.001), but not disease severity (P = 0.058), had a significant effect on diagnostic ability. At the sample mean age (60.9 years), AUCs for arbitrary values of intereye difference in SAP mean deviation (MD) of 0, 5, 10, and 15 dB were 0.58, 0.71, 0.82, and 0.90, respectively. The mean intereye difference in MD was 2.2±3.1 dB. The best combination of parameters had an AUC of 0.85; however, the cross-validated bias-corrected AUC for these parameters was only 0.74.ConclusionsAlthough the pupillograph had a good ability to detect glaucoma in the presence of asymmetric disease, it performed poorly in those with symmetric disease.
| S-EPMC4047189 | biostudies-literature
Project description:BackgroundAudiovisual streaming technologies allow detailed remote patient assessment and have been suggested to change management and enhance triage. The advent of wearable, head-mounted devices (HMDs) permits advanced teletoxicology at a relatively low cost. A previously published pilot study supports the feasibility of using the HMD Google Glass® (Google Inc.; Mountain View, CA) for teletoxicology consultation. This study examines the reliability, accuracy, and precision of the poisoned patient assessment when performed remotely via Google Glass®.MethodsA prospective observational cohort study was performed on 50 patients admitted to a tertiary care center inpatient toxicology service. Toxicology fellows wore Google Glass® and transmitted secure, real-time video and audio of the initial physical examination to a remote investigator not involved in the subject's care. High-resolution still photos of electrocardiograms (ECGs) were transmitted to the remote investigator. On-site and remote investigators recorded physical examination findings and ECG interpretation. Both investigators completed a brief survey about the acceptability and reliability of the streaming technology for each encounter. Kappa scores and simple agreement were calculated for each examination finding and electrocardiogram parameter. Reliability scores and reliability difference were calculated and compared for each encounter.ResultsData were available for analysis of 17 categories of examination and ECG findings. Simple agreement between on-site and remote investigators ranged from 68 to 100 % (median = 94 %, IQR = 10.5). Kappa scores could be calculated for 11/17 parameters and demonstrated slight to fair agreement for two parameters and moderate to almost perfect agreement for nine parameters (median = 0.653; substantial agreement). The lowest Kappa scores were for pupil size and response to light. On a 100-mm visual analog scale (VAS), mean comfort level was 93 and mean reliability rating was 89 for on-site investigators. For remote users, the mean comfort and reliability ratings were 99 and 86, respectively. The average difference in reliability scores between on-site and remote investigators was 2.6, with the difference increasing as reliability scores decreased.ConclusionRemote evaluation of poisoned patients via Google Glass® is possible with a high degree of agreement on examination findings and ECG interpretation. Evaluation of pupil size and response to light is limited, likely by the quality of streaming video. Users of Google Glass® for teletoxicology reported high levels of comfort with the technology and found it reliable, though as reported reliability decreased, remote users were most affected. Further study should compare patient-centered outcomes when using HMDs for consultation to those resulting from telephone consultation.
| S-EPMC5135678 | biostudies-literature
Project description:Polysomnography (PSG) is the current gold standard in high-resolution sleep monitoring; however, this method is obtrusive, expensive, and time-consuming. Conversely, commercially available wrist monitors such as ActiWatch can monitor sleep for multiple days and at low cost, but often overestimate sleep and cannot differentiate between sleep stages, such as rapid eye movement (REM) and non-REM. Wireless wearable sensors are a promising alternative for their portability and access to high-resolution data for customizable analytics. We present a multimodal sensor system measuring hand acceleration, electrocardiography, and distal skin temperature that outperforms the ActiWatch, detecting wake and sleep with a recall of 74.4% and 90.0%, respectively, as well as wake, non-REM, and REM with recall of 73.3%, 59.0%, and 56.0%, respectively. This approach will enable clinicians and researchers to more easily, accurately, and inexpensively assess long-term sleep patterns, diagnose sleep disorders, and monitor risk factors for disease in both laboratory and home settings.
| S-EPMC6925191 | biostudies-literature
Project description:Elevated core temperature constitutes an important biomarker for COVID-19 infection; however, no standards currently exist to monitor fever using wearable peripheral temperature sensors. Evidence that sensors could be used to develop fever monitoring capabilities would enable large-scale health-monitoring research and provide high-temporal resolution data on fever responses across heterogeneous populations. We launched the TemPredict study in March of 2020 to capture continuous physiological data, including peripheral temperature, from a commercially available wearable device during the novel coronavirus pandemic. We coupled these data with symptom reports and COVID-19 diagnosis data. Here we report findings from the first 50 subjects who reported COVID-19 infections. These cases provide the first evidence that illness-associated elevations in peripheral temperature are observable using wearable devices and correlate with self-reported fever. Our analyses support the hypothesis that wearable sensors can detect illnesses in the absence of symptom recognition. Finally, these data support the hypothesis that prediction of illness onset is possible using continuously generated physiological data collected by wearable sensors. Our findings should encourage further research into the role of wearable sensors in public health efforts aimed at illness detection, and underscore the importance of integrating temperature sensors into commercially available wearables.
| S-EPMC7736301 | biostudies-literature