Activity detection and classification are very important for autonomous monitoring of humans for applications, including assistive living, rehabilitation, and surveillance. Wearable sensors have ...found wide-spread use in recent years due to their ever-decreasing cost, ease of deployment and use, and ability to provide continuous monitoring as opposed to sensors installed at fixed locations. Since many smart phones are now equipped with a variety of sensors, such as accelerometer, gyroscope, and camera, it has become more feasible to develop activity monitoring algorithms employing one or more of these sensors with increased accessibility. We provide a complete and comprehensive survey on activity classification with wearable sensors, covering a variety of sensing modalities, including accelerometer, gyroscope, pressure sensors, and camera- and depth-based systems. We discuss differences in activity types tackled by this breadth of sensing modalities. For example, accelerometer, gyroscope, and magnetometer systems have a history of addressing whole body motion or global type activities, whereas camera systems provide the context necessary to classify local interactions, or interactions of individuals with objects. We also found that these single sensing modalities laid the foundation for hybrid works that tackle a mix of global and local interaction-type activities. In addition to the type of sensors and type of activities classified, we provide details on each wearable system that include on-body sensor location, employed learning approach, and extent of experimental setup. We further discuss where the processing is performed, i.e., local versus remote processing, for different systems. This is one of the first surveys to provide such breadth of coverage across different wearable sensor systems for activity classification.
Robust and reliable detection of falls is crucial especially for elderly activity monitoring systems. In this letter, we present a fall detection system using wearable devices, e.g., smartphones, and ...tablets, equipped with cameras and accelerometers. Since the portable device is worn by the subject, monitoring is not limited to confined areas, and extends to wherever the subject may travel, as opposed to static sensors installed in certain rooms. Moreover, a camera provides an abundance of information, and the results presented here show that fusing camera and accelerometer data not only increases the detection rate, but also decreases the number of false alarms compared to only accelerometer-based or only camera-based systems. We employ histograms of edge orientations together with the gradient local binary patterns for the camera-based part of fall detection. We compared the performance of the proposed method with that of using original histograms of oriented gradients (HOG) as well as a modified version of HOG. Experimental results show that the proposed method outperforms using original HOG and modified HOG, and provides lower false positive rates for the camera-based detection. Moreover, we have employed an accelerometer-based fall detection method, and fused these two sensor modalities to have a robust fall detection system. Experimental results and trials with actual Samsung Galaxy phones show that the proposed method, combining two different sensor modalities, provides much higher sensitivity, and a significant decrease in the number of false positives during daily activities, compared to accelerometer-only and camera-only methods.
Robust detection of events and activities, such as falling, sitting, and lying down, is a key to a reliable elderly activity monitoring system. While fast and precise detection of falls is critical ...in providing immediate medical attention, other activities like sitting and lying down can provide valuable information for early diagnosis of potential health problems. In this paper, we present a fall detection and activity classification system using wearable cameras. Since the camera is worn by the subject, monitoring is not limited to confined areas, and extends to wherever the subject may go including indoors and outdoors. Furthermore, since the captured images are not of the subject, privacy concerns are alleviated. We present a fall detection algorithm employing histograms of edge orientations and strengths, and propose an optical flow-based method for activity classification. The first set of experiments has been performed with prerecorded video sequences from eight different subjects wearing a camera on their waist. Each subject performed around 40 trials, which included falling, sitting, and lying down. Moreover, an embedded smart camera implementation of the algorithm was also tested on a CITRIC platform with subjects wearing the CITRIC camera, and each performing 50 falls and 30 non-fall activities. Experimental results show the success of the proposed method.
Dilation of one or more coronary artery segments to a diameter at least 1.5 times that of a normal adjacent segment is referred to as coronary artery ectasia (CAE). Adropin is a protein involved in ...endothelial function and is shown to have a protective effect on the regulation of cardiac functions. Atherosclerosis and endothelial dysfunction play an important role in the development of CAE. The aim of this study was to investigate the association between serum adropin levels and isolated CAE.
Patients with stable angina pectoris who underwent coronary angiography (CAG) between August 2017 and July 2018 were evaluated prospectively. A total of 92 subjects were included in the study-40 patients over 18 years old and diagnosed with isolated CAE based on CAG findings and a control group of 52 patients.
Serum adropin level was found to be significantly lower in the isolated CAE group compared to the control group (1019.57 pg/mL and 1151.10 pg/mL, respectively, p=0.010). The isolated CAE group also exhibited a significantly higher mean platelet volume than that in the control group (10.75 fL and 10.17 fL, respectively, p=0.011).
Our results show that there is an association between low serum adropin level and isolated CAE.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Milkweed (Asclepias spp.) are host plants of monarch butterflies (Danaus plexippus). It is important to detect milkweed plant locations to assess the status and trends of monarch habitat in support ...of monarch conservation programs. In this paper, we describe autonomous detection of milkweed plants using cameras mounted to vehicles. For detection, we used both aggregated channel features (ACF) for running the detectors on embedded computing platforms with central processing unit and faster region‐based convolutional neural network (Faster R‐CNN) with a ResNet architecture‐based detector that is suitable for graphics processing unit optimized processing. The ACF‐based model produced 0.89 mean average precision (mAP) on the training dataset and 0.29 mAP on the test dataset, whereas the ResNet‐based Faster R‐CNN model provided 0.98 mAP on training and 0.44 mAP on the test dataset. The detections were used to calculate approximate densities of milkweed plants in geo‐referenced locations based on global positioning system point correspondences of recorded images. Probability‐of‐count distributions are compared for the actual milkweed plant locations near roadsides. This is one of the first examples of using automated milkweed plant detection and density mapping using a vehicle‐mounted camera.
Timely, precise, and reliable detection of fall events is very important for systems monitoring activities of elderly people, especially the ones living independently. In this paper, we propose an ...autonomous fall detection system by taking a completely different view compared with existing vision-based activity monitoring systems and applying a reverse approach. In our system, in contrast with static sensors installed at fixed locations, the camera is worn by the subject, and thus, monitoring is not limited only to areas where the sensors are located and extends to wherever the subject may travel. Moreover, the camera provides a richer set of data and helps lower the false positive rates compared with accelerometer-only systems. We employ a modified version of the histograms of oriented gradients (HOG) approach together with the gradient local binary patterns (GLBP). It is shown that, with the same training set, the GLBP feature is more descriptive and discriminative than HOG, histograms of template, and semantic local binary patterns. Moreover, we autonomously compute a threshold, for the detection of fall events, from the training data based on relative entropy, which is a member of Ali-Silvey distance measures. Experiments are performed with ten different people and a total of around 300 associated fall events indoors and outdoors. Experimental results show that, with the autonomously computed threshold, the proposed method provides 93.78% and 89.8% accuracy for detecting falls with indoor and outdoor experiments, respectively.
Rakı is a traditional and Protected Designation of Origin (PDO) alcoholic beverage that is distilled from grape distillate with Pimpinella anisum L. in copper pot stills in Turkey. This study focused ...on the development of a sensory lexicon, a sensory wheel, using a consensus approach and the determination of major volatiles by GC-FID/MS for Rakı. A total of 37 Rakı samples representing all producers were used for volatile and sensory evaluation. The experts identified 78 attributes and references for the lexicon. The main attributes were spicy, anise, sweet, resinous, fruity, dry fruit, floral, head&tail aroma and white colour. The Rakı sensory wheel was created to provide a graphical display of its sensory attributes. For validation of the lexicon, 18 samples were evaluated using descriptive analysis. The results were subjected to PCA to examine the relationship of the samples with the defined sensory attributes. The PCA results show that there is a significant relationship between the Rakı categories and sensory terms and flavour intensities. The GC-MS analyses depicted the following major volatile compounds n-propanol, 2-methyl-1-propanol, 2 and 3-methyl-1-butanol, ethyl-acetate, acetal, acetaldehyde, trans-anethol and estragole. The characterization of the product using its most distinctive sensory descriptors are important tool and can be used for the industry, marketing, consumer education and scientists.
Bu araştırmanın ilgi alanı, Anadolu’da Selçuklu egemenlik çağında örgütlenmiş mekânsal ve işlevsel kademelenme gösteren kentler sistemi ve ulaşım ağının, “kentleşme koridoru” olarak
tanımlanan ana ...eksen ya da omurgasının belirlenmesidir. Başka bir ifadeyle, Selçuklu kentleşmesi olarak tanımlanan XII. yüzyıl başından XIII. yüzyıl sonuna dek uzanan süreçte Anadolu’da örgütlenmiş kentler sistemi ve ulaşım ağının ağırlık merkezinin belirlenmesidir. Araştırmanın yöntem kurgusu üç aşamalı bir çözümleme sürecine dayandırılmıştır. Birinci aşama, Selçuklu kentler sistemi ve ulaşım ağının omurgası olarak tanımlanan kentleşme koridorunun belirlenmesinde kullanılabilecek ölçütlerin saptanmasıdır. İkinci aşama, Selçuklu dönemine ilişkin vakâyî-name, vakıf-name ve kitabe gibi özgün kaynaklar ile arkeolojik buluntu ve mimari kalıtlardan oluşan bilgi birikiminin belirlenen her bir ölçüt düzeyinde sayısal yoğunluk değerleri açısından ayrıntıda çözümlenmesidir. Üçüncü aşama ise; her bir ölçüt düzeyinde elde edilen bulguların harita üzerinde görselleştirilerek, değerlendirilmesidir. Yapılan değerlendirmeler sonucunda, Konya-Kayseri-Sivas güzergâhının Selçuklu çağında Anadolu’nun sosyal-kültürel ve ekonomik açıdan en gelişmiş kentlerinin konumlandığı “kentleşme koridoru” olarak tanımlanan kentsel yığılma koridoru olduğu belirlenmiştir.
•Type 1 diabetes presence alone is not associated with more unsafe stopping.•Acute hyperglycemia is strongly associated with more unsafe stopping.•More data is needed to link acute hypoglycemia and ...unsafe stopping.•Both hypo- and hyperglycemia should be considered in diabetes driver evaluation.
Diabetes is a major public health challenge, affecting millions of people worldwide. Abnormal physiology in diabetes, particularly hypoglycemia, can cause driver impairments that affect safe driving. While diabetes driver safety has been previously researched, few studies link real-time physiologic changes in drivers with diabetes to objective real-world driver safety, particularly at high-risk areas like intersections. To address this, we investigated the role of acute physiologic changes in drivers with type 1 diabetes mellitus (T1DM) on safe stopping at stop intersections.
18 T1DM drivers (21–52 years, μ = 31.2 years) and 14 controls (21–55 years, μ = 33.4 years) participated in a 4-week naturalistic driving study. At induction, each participant’s personal vehicle was instrumented with a camera and sensor system to collect driving data (e.g., GPS, video, speed). Video was processed with computer vision algorithms detecting traffic elements (e.g., traffic signals, stop signs). Stop intersections were geolocated with clustering methods, state intersection databases, and manual review. Videos showing driver stop intersection approaches were extracted and manually reviewed to classify stopping behavior (full, rolling, and no stop) and intersection traffic characteristics.
Mixed-effects logistic regression models determined how diabetes driver stopping safety (safe vs. unsafe stop) was affected by 1) disease and 2) at-risk, acute physiology (hypo- and hyperglycemia). Diabetes drivers who were acutely hyperglycemic (≥ 300 mg/dL) had 2.37 increased odds of unsafe stopping (95% CI: 1.26–4.47, p = 0.008) compared to those with normal physiology. Acute hypoglycemia did not associate with unsafe stopping (p = 0.537), however the lower frequency of hypoglycemia (vs. hyperglycemia) warrants a larger sample of drivers to investigate this effect. Critically, presence of diabetes alone did not associate with unsafe stopping, underscoring the need to evaluate driver physiology in licensing guidelines.
This study links acute, abnormal physiologic fluctuations in drivers with diabetes to driver safety based on unsafe stopping at stop-controlled intersections, providing recommendations for clinicians aimed at improving patient safety, fair licensing guidelines, and targets for developing advanced driver assistance systems.
Bu araştırmanın amacı; Türkiye tarihsel kentlerinden Birgi yerleşmesinin kültürel ve doğal mirasdeğerlerinin birlikteliğinden oluşan mekânsal karakteristik ve işlevsel kimlik değerleri ...eşliğindekoruma deneyimlerinin irdelenmesidir. Bu irdelemelerin; Türkiye tarihsel kentlerinin geleceği üzerineüretilecek kültürel miras odaklı koruma politika ve stratejilere yol haritası olarak yöntem düzeyindekatkı koyacağı, diğer yönüyle, tarihsel kentlerde koruma sürecinde karşılaşılabilecek (olası) ortak sorunlaraçözüm arayışları açısından yerel yönetimler düzeyinde bilgi aktarımı–paylaşımı yoluyla katkısağlayacağı düşünülmektedir. Dolayısıyla; Birgi koruma deneyiminin, ulusal–bölgesel düzeyde kurumsalörgütlenme–katılım ve finansman alternatiflerine yönelik kurumlar–arası işbirliği–ortaklıklaraçısından yerel yönetimlere koruma yönetişimi düzeyinde önemli bir örnek oluşturacağı söylenebilir.Bu çerçevede, Birgi Belediyesi’nin ulusal–bölgesel ölçekte kurduğu ortaklıkların, Avrupa Birliği Euromedve Eurocities ya da Citta Slow ve European Walled Towns gibi uluslararası kurum ya da ortaklıklar/birlikler eşliğinde küresel düzleme taşınması, yerleşmenin küresel düzeyde markalaşma ve tanınırlık–bilinirlik süreçlerine önemli katkılar sağlayacaktır. Araştırma; Birgi yerleşmesini üç aşamalıbir değerlendirme sürecinde ele almaktadır: Birincisi, yazılı–sözel ve görsel kaynaklar kullanılarakyerleşmenin mekânsal karakteristik ve işlevsel kimlik değerlerinin tanımlanmasıdır. İkincisi; korumaodaklı planlama ve uygulama deneyimlerinin, tarihsel izlence eşliğinde ayrıntıda açıklanmasıdır.Üçüncüsü ise; Birgi Belediyesi tarafından gerçekleştirilen veya planlanan sosyal–kültürel, ekonomikve mekânsal içerikli projelerin, kültürel miras değerlerinin korunması sürecindeki katkılarının irdelenmesidir.
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