Sparse natural gesture spotting in free living to monitor drinking with wrist-worn inertial sensors

2018 ◽  
Author(s):  
Giovanni Schiboni ◽  
Oliver Amft
Keyword(s):  
Inertial Sensors ◽  
Free Living ◽  
Gesture Spotting

scholarly journals Inertial sensor-based centripetal acceleration as a correlate for lateral margin of stability during walking and turning

2019 ◽  
Author(s):  
Peter C. Fino ◽  
Fay B. Horak ◽  
Carolin Curtze
Keyword(s):  
Lumbar Spine ◽  
Mechanical Stability ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Center Of Mass ◽  
Free Living ◽  
Centripetal Acceleration ◽  
Margin Of Stability ◽  
Subsequent Step ◽  
Single Sensor

AbstractThere is growing interest in using inertial sensors to continuously monitor gait during free-living mobility. Inertial sensors can provide many gait measures, but they struggle to capture the spatial stability of the center-of-mass due to limitations estimating sensor-to-sensor distance. While the margin of stability (MoS) is an established outcome describing the instantaneous mechanical stability of gait relating to fall-risk, methods to estimate the MoS from inertial sensors have been lacking. Here, we developed and tested a framework, based on centripetal acceleration, to determine a correlate for the lateral MoS using inertial sensors during walking with or without turning. Using three synchronized sensors located bilaterally on the feet and lumbar spine, the average centripetal acceleration over the subsequent step can be used as a correlate for lateral MoS. Relying only on a single sensor on the lumbar spine yielded similar results if the stance foot can be determined from other means. Additionally, the centripetal acceleration correlate of lateral MoS demonstrates clear differences between walking and turning, inside and outside turning limbs, and speed. While limitations and assumptions need to be considered when implemented in practice, this method presents a novel correlate for the lateral MoS during walking and turning using inertial sensors, although further validation is required for other activities and populations.

scholarly journals Validity of a Smart-Glasses-Based Step-Count Measure during Simulated Free-Living Conditions

Information ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 404
Author(s):  
Alessia Cristiano ◽  
Alberto Sanna ◽  
Diana Trojaniello
Keyword(s):  
Inertial Sensors ◽  
Percentage Error ◽  
Free Living ◽  
Step Counter ◽  
Smart Glasses ◽  
Counting Functions ◽  
Step Counting ◽  
Key Features ◽  
Free Living Conditions ◽  
The Ideal

Step counting represents a valuable approach to monitor the amount of daily physical activity. The feet, wrist and trunk have been demonstrated as the ideal locations to automatically detect the number of steps through body-worn devices (i.e., step counters). Key features of such devices are high usability, practicality and unobtrusiveness. Therefore, the opportunity to integrate step-counting functions in daily worn accessories represents one of the recent and most important challenges. In this context, the present study aimed to investigate the validity of a smart-glasses-based step-counter measure by comparing their performances against the most popular commercial step counters. To this purpose, smart glasses data from 26 healthy subjects performing simulated free-living walking conditions along a predefined path were collected. Reference measures from inertial sensors mounted on the subjects’ ankles and data from commercial (waist- and wrists-worn) step counters were acquired during the tests. The results showed an overall percentage error of 1%. In conclusion, the proposed smart glasses could be considered an accurate step counter, showing performances comparable to the most common commercial step counters.

scholarly journals Continuous home monitoring of Parkinson’s disease using inertial sensors: A systematic review

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246528
Author(s):  
Marco Sica ◽  
Salvatore Tedesco ◽  
Colum Crowe ◽  
Lorna Kenny ◽  
Kevin Moore ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Inertial Sensors ◽  
Wearable Sensors ◽  
Home Monitoring ◽  
Relevant Information ◽  
Step Length ◽  
Living Environment ◽  
Free Living ◽  
Gait Impairments

Parkinson’s disease (PD) is a progressive neurological disorder of the central nervous system that deteriorates motor functions, while it is also accompanied by a large diversity of non-motor symptoms such as cognitive impairment and mood changes, hallucinations, and sleep disturbance. Parkinsonism is evaluated during clinical examinations and appropriate medical treatments are directed towards alleviating symptoms. Tri-axial accelerometers, gyroscopes, and magnetometers could be adopted to support clinicians in the decision-making process by objectively quantifying the patient’s condition. In this context, at-home data collections aim to capture motor function during daily living and unobstructedly assess the patients’ status and the disease’s symptoms for prolonged time periods. This review aims to collate existing literature on PD monitoring using inertial sensors while it focuses on papers with at least one free-living data capture unsupervised either directly or via videotapes. Twenty-four papers were selected at the end of the process: fourteen investigated gait impairments, eight of which focused on walking, three on turning, two on falls, and one on physical activity; ten articles on the other hand examined symptoms, including bradykinesia, tremor, dyskinesia, and motor state fluctuations in the on/off phenomenon. In summary, inertial sensors are capable of gathering data over a long period of time and have the potential to facilitate the monitoring of people with Parkinson’s, providing relevant information about their motor status. Concerning gait impairments, kinematic parameters (such as duration of gait cycle, step length, and velocity) were typically used to discern PD from healthy subjects, whereas for symptoms’ assessment, researchers were capable of achieving accuracies of over 90% in a free-living environment. Further investigations should be focused on the development of ad-hoc hardware and software capable of providing real-time feedback to clinicians and patients. In addition, features such as the wearability of the system and user comfort, set-up process, and instructions for use, need to be strongly considered in the development of wearable sensors for PD monitoring.

Gesture spotting with body-worn inertial sensors to detect user activities

2008 ◽  
Vol 41 (6) ◽  
pp. 2010-2024 ◽  
Author(s):  
Holger Junker ◽  
Oliver Amft ◽  
Paul Lukowicz ◽  
Gerhard Tröster
Keyword(s):  
Inertial Sensors ◽  
User Activities ◽  
Gesture Spotting

mTeeth

2021 ◽  
Vol 5 (2) ◽  
pp. 1-25
Author(s):  
Sayma Akther ◽  
Nazir Saleheen ◽  
Mithun Saha ◽  
Vivek Shetty ◽  
Santosh Kumar
Keyword(s):  
Machine Learning ◽  
Natural Environment ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Living Environment ◽  
Sensor Data ◽  
Oral Diseases ◽  
Free Living ◽  
Manual Toothbrush ◽  
The Impact

Ensuring that all the teeth surfaces are adequately covered during daily brushing can reduce the risk of several oral diseases. In this paper, we propose the mTeeth model to detect teeth surfaces being brushed with a manual toothbrush in the natural free-living environment using wrist-worn inertial sensors. To unambiguously label sensor data corresponding to different surfaces and capture all transitions that last only milliseconds, we present a lightweight method to detect the micro-event of brushing strokes that cleanly demarcates transitions among brushing surfaces. Using features extracted from brushing strokes, we propose a Bayesian Ensemble method that leverages the natural hierarchy among teeth surfaces and patterns of transition among them. For training and testing, we enrich a publicly-available wrist-worn inertial sensor dataset collected from the natural environment with time-synchronized precise labels of brushing surface timings and moments of transition. We annotate 10,230 instances of brushing on different surfaces from 114 episodes and evaluate the impact of wide between-person and within-person between-episode variability on machine learning model's performance for brushing surface detection.

Ultrastructure of neuromuscular relationships in the canine heartworm (dirofilaria immitis)

1986 ◽  
Vol 44 ◽  
pp. 278-279
Author(s):  
W. L. Steffens ◽  
Nancy B. Roberts ◽  
J. M. Bowen
Keyword(s):  
Dirofilaria Immitis ◽  
Domestic Dogs ◽  
Structural Description ◽  
Pharmacological Effects ◽  
Free Living ◽  
Canine Heartworm ◽  
The World ◽  
Synaptic Region ◽  
Muscle Innervation ◽  
Insight Into

The canine heartworm is a common and serious nematode parasite of domestic dogs in many parts of the world. Although nematode neuroanatomy is fairly well documented, the emphasis has been on sensory anatomy and primarily in free-living soil species and ascarids. Lee and Miller reported on the muscular anatomy in the heartworm, but provided little insight into the peripheral nervous system or myoneural relationships. The classical fine-structural description of nematode muscle innervation is Rosenbluth's earlier work in Ascaris. Since the pharmacological effects of some nematacides currently being developed are neuromuscular in nature, a better understanding of heartworm myoneural anatomy, particularly in reference to the synaptic region is warranted.

Lead and lead toxicity in domestic and free living birds

2003 ◽  
Vol 32 (1) ◽  
pp. 3-13 ◽  
Author(s):  
N. De Francisco ◽  
N. De Francisco ◽  
N. De Francisco
Keyword(s):  
Lead Toxicity ◽  
Free Living

Platelet Aggregation in Finnish Men and Its Relation to Fatty Acids in Platelets, Plasma and Adipose Tissue

1985 ◽  
Vol 54 (03) ◽  
pp. 563-569 ◽  
Author(s):  
M K Salo ◽  
E Vartiainen ◽  
P Puska ◽  
T Nikkari
Keyword(s):  
Fatty Acids ◽  
Adipose Tissue ◽  
Fatty Acid Composition ◽  
Fatty Acid ◽  
Platelet Aggregation ◽  
Acid Composition ◽  
Saturated Fatty Acids ◽  
Free Living ◽  
Ω3 Fatty Acids ◽  
Induced Aggregation

SummaryPlatelet aggregation and its relation to fatty acid composition of platelets, plasma and adipose tissue was determined in 196 randomly selected, free-living, 40-49-year-old men in two regions of Finland (east and southwest) with a nearly twofold difference in the IHD rate.There were no significant east-southwest differences in platelet aggregation induced with ADP, thrombin or epinephrine. ADP-induced platelet secondary aggregation showed significant negative associations with all C20-C22 ω3-fatty acids in platelets (r = -0.26 - -0.40) and with the platelet 20: 5ω3/20: 4ω 6 and ω3/ ω6 ratios, but significant positive correlations with the contents of 18:2 in adipose tissue (r = 0.20) and plasma triglycerides (TG) (r = 0.29). Epinephrine-induced aggregation correlated negatively with 20: 5ω 3 in plasma cholesteryl esters (CE) (r = -0.23) and TG (r = -0.29), and positively with the total percentage of saturated fatty acids in platelets (r = 0.33), but had no significant correlations with any of the ω6-fatty acids. Thrombin-induced aggregation correlated negatively with the ω3/6ω ratio in adipose tissue (r = -0.25) and the 20: 3ω6/20: 4ω 6 ratio in plasma CE (r = -0.27) and free fatty acids (FFA) (r = -0.23), and positively with adipose tissue 18:2 (r = 0.23) and 20:4ω6 (r = 0.22) in plasma phospholipids (PL).The percentages of prostanoid precursors in platelet lipids, i. e. 20: 3ω 6, 20: 4ω 6 and 20 :5ω 3, correlated best with the same fatty acids in plasma CE (r = 0.32 - 0.77) and PL (r = 0.28 - 0.74). Platelet 20: 5ω 3 had highly significant negative correlations with the percentage of 18:2 in adipose tissue and all plasma lipid fractions (r = -0.35 - -0.44).These results suggest that, among a free-living population, relatively small changes in the fatty acid composition of plasma and platelets may be reflected in significant differences in platelet aggregation, and that an increase in linoleate-rich vegetable fat in the diet may not affect platelet function favourably unless it is accompanied by an adequate supply of ω3 fatty acids.

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