Objective To estimate the prevalence of unknown atrial fibrillation(AF)in the elderly population of the Veneto Region,Italy.Methods 1820 patients aged≥65 years with no history of AF and not anticoagulated were enroll...Objective To estimate the prevalence of unknown atrial fibrillation(AF)in the elderly population of the Veneto Region,Italy.Methods 1820 patients aged≥65 years with no history of AF and not anticoagulated were enrolled in primary-care settings.They underwent an opportunistic electrocardiogram screening with a handheld device(My Diagnostick)designed to specifically detect AF.The electrocardiogram recordings were reviewed by the researchers,who confirmed the presence of AF.Results The device detected an arrhythmia in 143 patients,which was confirmed as AF in 101/143(70.6%),with an overall prevalence of AF of 5.5%(101/1820).Prevalence of unknown AF resulted in 3.6%in patients aged 65–74 years,and 7.5%in patients age 75 or older,and increased according to CHA2 DS2-VASc score:3.5%in patients with a score of 1 or 2,5.6%in patients with a score of 3,7.0%in patients with a score of 4,and 7.2%in patients with a score≥5.The detection rate was significantly higher in patients with mild symptoms compared to asymptomatic counterparts(24.1%vs.4.0%,P<0.0001).At multivariate analysis,congestive heart failure and age≥75 years-old were independent predictors for screen-detected AF.Conclusions An opportunistic screening with handheld device revealed an unexpectedly high prevalence of unknown AF in elderly patients with mild symptoms.Prevalence increased with age and CHA2DS2-VASc score.展开更多
BACKGROUND:The use of ultrasound(US)within healthcare has inspired the development of new US technology.There have been few studies comparing the use of handheld US to standard US for medical education.This research a...BACKGROUND:The use of ultrasound(US)within healthcare has inspired the development of new US technology.There have been few studies comparing the use of handheld US to standard US for medical education.This research aims to determine whether a handheld US device can provide a comparable primary learning experience to that of a standard US machine.METHODS:Over two days of instruction,participants were taught and evaluated on core US fundamentals.The standard group received instruction on standard US machines,while the handheld group received instruction on handheld US devices.Participants completed a qualitative survey regarding their experience.Six hundred and four images were obtained and graded by two emergency medicine physicians.RESULTS:A total of 119 Swiss medical students were enrolled in our study.There was no statistically significant difference in the US assessment measurements,except for faster endpoint septal separation(EPSS)vascular setup time in the handheld group(P=0.001).There was no statistically significant difference in participants’perceived difficulty of US learning(P=0.198),comfort level(P=0.188),or self-estimated capability to perform US in the future(P=0.442).There was no statistically significant difference in the percentage of correctly obtained images(P=0.211)or images that were clinically useful(P=0.256).The median quality score of images obtained by the standard group was eight compared to seven in handheld group(P<0.01).CONCLUSION:Our data suggest a handheld US machine can perform as well as a standard US machine as an educational tool despite sacrifices in image quality.展开更多
AIM: To explore the performance in diabetic retinopathy(DR) screening of artificial intelligence(AI) system by evaluating the image quality of a handheld Optomed Aurora fundus camera in comparison to traditional table...AIM: To explore the performance in diabetic retinopathy(DR) screening of artificial intelligence(AI) system by evaluating the image quality of a handheld Optomed Aurora fundus camera in comparison to traditional tabletop fundus cameras and the diagnostic accuracy of DR of the two modalities. METHODS: Overall, 630 eyes were included from three centers and screened by a handheld camera(Aurora, Optomed, Oulu, Finland) and a table-top camera. Image quality was graded by three masked and experienced ophthalmologists. The diagnostic accuracy of the handheld camera and AI system was evaluated in assessing DR lesions and referable DR.RESULTS: Under nonmydriasis status, the handheld fundus camera had better image quality in centration, clarity, and visible range(1.47, 1.48, and 1.40) than conventional tabletop cameras(1.30, 1.28, and 1.18;P<0.001). Detection of retinal hemorrhage, hard exudation,and macular edema were comparable between the two modalities, in principle, with the area under the curve of the handheld fundus camera slightly lower. The sensitivity and specificity for the detection of referable DR with the handheld camera were 82.1%(95%CI: 72.1%-92.2%) and 97.4%(95%CI: 95.4%-99.5%), respectively. The performance of AI detection of DR using the Phoebus Algorithm was satisfactory;however, Phoebus showed a high sensitivity(88.2%, 95%CI: 79.4%-97.1%) and low specificity(40.7%, 95%CI: 34.1%-47.2%) when detecting referable DR.CONCLUSION: The handheld Aurora fundus camera combined with autonomous AI system is well-suited in DR screening without mydriasis because of its high sensitivity of DR detection as well as its image quality, but its specificity needs to be improved with better modeling of the data. Use of this new system is safe and effective in the detection of referable DR in real world practice.展开更多
Sustainable forest management heavily relies on the accurate estimation of tree parameters.Among others,the diameter at breast height(DBH) is important for extracting the volume and mass of an individual tree.For syst...Sustainable forest management heavily relies on the accurate estimation of tree parameters.Among others,the diameter at breast height(DBH) is important for extracting the volume and mass of an individual tree.For systematically estimating the volume of entire plots,airborne laser scanning(ALS) data are used.The estimation model is frequently calibrated using manual DBH measurements or static terrestrial laser scans(STLS) of sample plots.Although reliable,this method is time-consuming,which greatly hampers its use.Here,a handheld mobile terrestrial laser scanning(HMTLS) was demonstrated to be a useful alternative technique to precisely and efficiently calculate DBH.Different data acquisition techniques were applied at a sample plot,then the resulting parameters were comparatively analysed.The calculated DBH values were comparable to the manual measurements for HMTLS,STLS,and ALS data sets.Given the comparability of the extracted parameters,with a reduced point density of HTMLS compared to STLS data,and the reasonable increase of performance,with a reduction of acquisition time with a factor of5 compared to conventional STLS techniques and a factor of3 compared to manual measurements,HMTLS is considered a useful alternative technique.展开更多
This paper presents a handheld 3D vision-based scanner for small objects by using Kinect. It is different from the previous color-glove-based approaches which require segmenting the target object. First,we eliminate t...This paper presents a handheld 3D vision-based scanner for small objects by using Kinect. It is different from the previous color-glove-based approaches which require segmenting the target object. First,we eliminate the noises and the outliers caused by holding hands. Second,we apply Kinect-fusion algorithm and truncated signed distance function(TSDF) to represent 3D surfaces. Third,we propose a modified integration strategy to eliminate the hand effect. Fourth,we take advantage of the parallel computation of GPUs for real-time operation. The major contributions of this paper are(1) the registration precision is improved,(2) the offline amendment and loop closure operation are not required,and(3) concave 3D object reconstruction is feasible. Index TermsHandheld 3D scanning,Kinect-fusion,Truncated signed distance function(TSDF). 1. Introduction Recently,the sensor-based 3D model reconstruction methods have been proposed[1]. The sensor devices have different properties so that the 3D reconstruction algorithms vary accordingly. The commonly used sensor devices are time-of-flight(To F) cameras[2]-[4],laser scanners[5],and structured light scanners[6],[7]. Lasers have gained a reputation for accuracy; however,care must be taken to use eye-safe lasers when operating in proximity to humans. For an interactive system,the structured light scanner which is basically a passive vision-based sensor device is superior because it provides a 2D depth image per frame and is more accurate than that of a To F camera. Here,we present a real-time 3D scanner using the depth images captured by Kinect.展开更多
This work focuses on a brief discussion of new concepts of using smartphone sensors for 3D painting in virtual or augmented reality. Motivation of this research comes from the idea of using different types of sensors ...This work focuses on a brief discussion of new concepts of using smartphone sensors for 3D painting in virtual or augmented reality. Motivation of this research comes from the idea of using different types of sensors which exist in our smartphones such as accelerometer, gyroscope, magnetometer etc. to track the position for painting in virtual reality, like Google Tilt Brush, but cost effectively. Research studies till date on estimating position and localization and tracking have been thoroughly reviewed to find the appropriate algorithm which will provide accurate result with minimum drift error. Sensor fusion, Inertial Measurement Unit (IMU), MEMS inertial sensor, Kalman filter based global translational localization systems are studied. It is observed, prevailing approaches consist issues such as stability, random bias drift, noisy acceleration output, position estimation error, robustness or accuracy, cost effectiveness etc. Moreover, issues with motions that do not follow laws of physics, bandwidth, restrictive nature of assumptions, scale optimization for large space are noticed as well. Advantages of such smartphone sensor based position estimation approaches include, less memory demand, very fast operation, making them well suited for real time problems and embedded systems. Being independent of the size of the system, they can work effectively for high dimensional systems as well. Through study of these approaches it is observed, extended Kalman filter gives the highest accuracy with reduced requirement of excess hardware during tracking. It renders better and faster result when used in accelerometer sensor. With the aid of various software, error accuracy can be increased further as well.展开更多
Handheld optical sensors recently have been introduced to the agricultural market.These handheld sensors are able to provide operators with Normalized Difference Vegetative Index(NDVI)data when cloud cover prevents ac...Handheld optical sensors recently have been introduced to the agricultural market.These handheld sensors are able to provide operators with Normalized Difference Vegetative Index(NDVI)data when cloud cover prevents acquisition of satellite or aerial images.This research addressed the sensitivity of the GreenSeeker handheld optical sensor to changes in orientation and height above a ryegrass canopy.Planter boxes were oriented both parallel and perpendicular to the light beam from the sensor head and heights of 30.5 cm(12”),61.0 cm(24”),91.5 cm(36”),122 cm(48”)and 152 cm(60”)were tested.Results indicated that the sensor was highly sensitive(P<0.0001)to both height above canopy and orientation of the sensor relative to the target.Operators should follow manufacturer’s recommendations on operating height range of 81-122 cm and orient the sensor head in-line with the target to obtain maximum signal response.展开更多
文摘Objective To estimate the prevalence of unknown atrial fibrillation(AF)in the elderly population of the Veneto Region,Italy.Methods 1820 patients aged≥65 years with no history of AF and not anticoagulated were enrolled in primary-care settings.They underwent an opportunistic electrocardiogram screening with a handheld device(My Diagnostick)designed to specifically detect AF.The electrocardiogram recordings were reviewed by the researchers,who confirmed the presence of AF.Results The device detected an arrhythmia in 143 patients,which was confirmed as AF in 101/143(70.6%),with an overall prevalence of AF of 5.5%(101/1820).Prevalence of unknown AF resulted in 3.6%in patients aged 65–74 years,and 7.5%in patients age 75 or older,and increased according to CHA2 DS2-VASc score:3.5%in patients with a score of 1 or 2,5.6%in patients with a score of 3,7.0%in patients with a score of 4,and 7.2%in patients with a score≥5.The detection rate was significantly higher in patients with mild symptoms compared to asymptomatic counterparts(24.1%vs.4.0%,P<0.0001).At multivariate analysis,congestive heart failure and age≥75 years-old were independent predictors for screen-detected AF.Conclusions An opportunistic screening with handheld device revealed an unexpectedly high prevalence of unknown AF in elderly patients with mild symptoms.Prevalence increased with age and CHA2DS2-VASc score.
文摘BACKGROUND:The use of ultrasound(US)within healthcare has inspired the development of new US technology.There have been few studies comparing the use of handheld US to standard US for medical education.This research aims to determine whether a handheld US device can provide a comparable primary learning experience to that of a standard US machine.METHODS:Over two days of instruction,participants were taught and evaluated on core US fundamentals.The standard group received instruction on standard US machines,while the handheld group received instruction on handheld US devices.Participants completed a qualitative survey regarding their experience.Six hundred and four images were obtained and graded by two emergency medicine physicians.RESULTS:A total of 119 Swiss medical students were enrolled in our study.There was no statistically significant difference in the US assessment measurements,except for faster endpoint septal separation(EPSS)vascular setup time in the handheld group(P=0.001).There was no statistically significant difference in participants’perceived difficulty of US learning(P=0.198),comfort level(P=0.188),or self-estimated capability to perform US in the future(P=0.442).There was no statistically significant difference in the percentage of correctly obtained images(P=0.211)or images that were clinically useful(P=0.256).The median quality score of images obtained by the standard group was eight compared to seven in handheld group(P<0.01).CONCLUSION:Our data suggest a handheld US machine can perform as well as a standard US machine as an educational tool despite sacrifices in image quality.
基金Supported by the National Natural Science Foundation of China(No.81970845)European Union’s Horizon 2020 research and innovation programme under grant agreement(No.778089)。
文摘AIM: To explore the performance in diabetic retinopathy(DR) screening of artificial intelligence(AI) system by evaluating the image quality of a handheld Optomed Aurora fundus camera in comparison to traditional tabletop fundus cameras and the diagnostic accuracy of DR of the two modalities. METHODS: Overall, 630 eyes were included from three centers and screened by a handheld camera(Aurora, Optomed, Oulu, Finland) and a table-top camera. Image quality was graded by three masked and experienced ophthalmologists. The diagnostic accuracy of the handheld camera and AI system was evaluated in assessing DR lesions and referable DR.RESULTS: Under nonmydriasis status, the handheld fundus camera had better image quality in centration, clarity, and visible range(1.47, 1.48, and 1.40) than conventional tabletop cameras(1.30, 1.28, and 1.18;P<0.001). Detection of retinal hemorrhage, hard exudation,and macular edema were comparable between the two modalities, in principle, with the area under the curve of the handheld fundus camera slightly lower. The sensitivity and specificity for the detection of referable DR with the handheld camera were 82.1%(95%CI: 72.1%-92.2%) and 97.4%(95%CI: 95.4%-99.5%), respectively. The performance of AI detection of DR using the Phoebus Algorithm was satisfactory;however, Phoebus showed a high sensitivity(88.2%, 95%CI: 79.4%-97.1%) and low specificity(40.7%, 95%CI: 34.1%-47.2%) when detecting referable DR.CONCLUSION: The handheld Aurora fundus camera combined with autonomous AI system is well-suited in DR screening without mydriasis because of its high sensitivity of DR detection as well as its image quality, but its specificity needs to be improved with better modeling of the data. Use of this new system is safe and effective in the detection of referable DR in real world practice.
基金funded by University College GhentGhent University。
文摘Sustainable forest management heavily relies on the accurate estimation of tree parameters.Among others,the diameter at breast height(DBH) is important for extracting the volume and mass of an individual tree.For systematically estimating the volume of entire plots,airborne laser scanning(ALS) data are used.The estimation model is frequently calibrated using manual DBH measurements or static terrestrial laser scans(STLS) of sample plots.Although reliable,this method is time-consuming,which greatly hampers its use.Here,a handheld mobile terrestrial laser scanning(HMTLS) was demonstrated to be a useful alternative technique to precisely and efficiently calculate DBH.Different data acquisition techniques were applied at a sample plot,then the resulting parameters were comparatively analysed.The calculated DBH values were comparable to the manual measurements for HMTLS,STLS,and ALS data sets.Given the comparability of the extracted parameters,with a reduced point density of HTMLS compared to STLS data,and the reasonable increase of performance,with a reduction of acquisition time with a factor of5 compared to conventional STLS techniques and a factor of3 compared to manual measurements,HMTLS is considered a useful alternative technique.
基金supported by the Ministry of Science and Technology of Taiwan under Grant No.MOST103-2221-E-468-006–MY1
文摘This paper presents a handheld 3D vision-based scanner for small objects by using Kinect. It is different from the previous color-glove-based approaches which require segmenting the target object. First,we eliminate the noises and the outliers caused by holding hands. Second,we apply Kinect-fusion algorithm and truncated signed distance function(TSDF) to represent 3D surfaces. Third,we propose a modified integration strategy to eliminate the hand effect. Fourth,we take advantage of the parallel computation of GPUs for real-time operation. The major contributions of this paper are(1) the registration precision is improved,(2) the offline amendment and loop closure operation are not required,and(3) concave 3D object reconstruction is feasible. Index TermsHandheld 3D scanning,Kinect-fusion,Truncated signed distance function(TSDF). 1. Introduction Recently,the sensor-based 3D model reconstruction methods have been proposed[1]. The sensor devices have different properties so that the 3D reconstruction algorithms vary accordingly. The commonly used sensor devices are time-of-flight(To F) cameras[2]-[4],laser scanners[5],and structured light scanners[6],[7]. Lasers have gained a reputation for accuracy; however,care must be taken to use eye-safe lasers when operating in proximity to humans. For an interactive system,the structured light scanner which is basically a passive vision-based sensor device is superior because it provides a 2D depth image per frame and is more accurate than that of a To F camera. Here,we present a real-time 3D scanner using the depth images captured by Kinect.
文摘This work focuses on a brief discussion of new concepts of using smartphone sensors for 3D painting in virtual or augmented reality. Motivation of this research comes from the idea of using different types of sensors which exist in our smartphones such as accelerometer, gyroscope, magnetometer etc. to track the position for painting in virtual reality, like Google Tilt Brush, but cost effectively. Research studies till date on estimating position and localization and tracking have been thoroughly reviewed to find the appropriate algorithm which will provide accurate result with minimum drift error. Sensor fusion, Inertial Measurement Unit (IMU), MEMS inertial sensor, Kalman filter based global translational localization systems are studied. It is observed, prevailing approaches consist issues such as stability, random bias drift, noisy acceleration output, position estimation error, robustness or accuracy, cost effectiveness etc. Moreover, issues with motions that do not follow laws of physics, bandwidth, restrictive nature of assumptions, scale optimization for large space are noticed as well. Advantages of such smartphone sensor based position estimation approaches include, less memory demand, very fast operation, making them well suited for real time problems and embedded systems. Being independent of the size of the system, they can work effectively for high dimensional systems as well. Through study of these approaches it is observed, extended Kalman filter gives the highest accuracy with reduced requirement of excess hardware during tracking. It renders better and faster result when used in accelerometer sensor. With the aid of various software, error accuracy can be increased further as well.
文摘Handheld optical sensors recently have been introduced to the agricultural market.These handheld sensors are able to provide operators with Normalized Difference Vegetative Index(NDVI)data when cloud cover prevents acquisition of satellite or aerial images.This research addressed the sensitivity of the GreenSeeker handheld optical sensor to changes in orientation and height above a ryegrass canopy.Planter boxes were oriented both parallel and perpendicular to the light beam from the sensor head and heights of 30.5 cm(12”),61.0 cm(24”),91.5 cm(36”),122 cm(48”)and 152 cm(60”)were tested.Results indicated that the sensor was highly sensitive(P<0.0001)to both height above canopy and orientation of the sensor relative to the target.Operators should follow manufacturer’s recommendations on operating height range of 81-122 cm and orient the sensor head in-line with the target to obtain maximum signal response.
