ArticleSensors (Basel, Switzerland)2018
Statistical Platform for Individualized Behavioral Analyses Using Biophysical Micro-Movement Spikes.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 23 citations in OpenAlex.
- Facial micro-movements as a proxy of increasingly erratic heart rate variability while experiencing pressure pain.Frontiers in neuroscience · 2026Article
- Setting Up Our Lab-in-a-Box: Paving the Road Towards Remote Data Collection for Scalable Personalized Biometrics.Journal of personalized medicine · 2025Article
- Hidden social and emotional competencies in autism spectrum disorders captured through the digital lens.Frontiers in psychiatry · 2025Article
- Digital screener of socio-motor agency balancing motor autonomy and motor control.Frontiers in human neuroscience · 2024Article
- The time is ripe for the renaissance of autism treatments: evidence from clinical practitioners.Frontiers in integrative neuroscience · 2023Article
- Motor Signatures in Digitized Cognitive and Memory Tests Enhances Characterization of Parkinson's Disease.Sensors (Basel, Switzerland) · 2022Article
- Digitized Autism Observation Diagnostic Schedule: Social Interactions beyond the Limits of the Naked Eye.Journal of personalized medicine · 2020Article
- Reframing Psychiatry for Precision Medicine.Journal of personalized medicine · 2020Article
- Aging with Autism Departs Greatly from Typical Aging.Sensors (Basel, Switzerland) · 2020Article
- Peripheral Network Connectivity Analyses for the Real-Time Tracking of Coupled Bodies in Motion.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wearable biosensors, such as those embedded in smart phones, can provide data to assess neuro-motor control in mobile settings, at homes, schools, workplaces and clinics. However, because most machine learning algorithms currently used to analyze such data require several steps that depend on human heuristics, the analyses become computationally expensive and rather subjective. Further, there is no standardized scale or set of tasks amenable to take advantage of such technology in ways that permit broad dissemination and reproducibility of results. Indeed, there is a critical need for fully objective automated analytical methods that easily handle the deluge of data these sensors output, while providing standardized scales amenable to apply across large sections of the population, to help promote personalized-mobile medicine. Here we use an open-access data set from Kaggle.com to illustrate the use of a new statistical platform and standardized data types applied to smart phone accelerometer and gyroscope data from 30 participants, performing six different activities. We report full distinction without confusion of the activities from the Kaggle set using a single parameter (linear acceleration or angular speed). We further extend the use of our platform to characterize data from commercially available smart shoes, using gait patterns within a set of experiments that probe nervous systems functioning and levels of motor control.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.