THE APPLICATION OF MACHINE LEARNING ON THE SENSORS OF SMARTPHONES TO DETECT FALLS IN REAL-TIME
Article Sidebar
Open full text
Issue Vol. 13 No. 2 (2023)
-
NOVEL HYBRID ALGORITHM USING CONVOLUTIONAL AUTOENCODER WITH SVM FOR ELECTRICAL IMPEDANCE TOMOGRAPHY AND ULTRASOUND COMPUTED TOMOGRAPHY
4-9
-
ANALYSIS OF POWER AND ENERGY PARAMETERS OF THE CONVEYOR INFRARED DRYER OF OIL-CONTAINING RAW MATERIALS
10-14
-
OPTIMIZATION OF RESOURCE ALLOCATION, EXPOSURE TIME AND ROTARY SPEED OF INCUBATIVE EGGS
15-19
-
DEVELOPMENT OF AN APPLICATION FOR THE THERMAL PROCESSING OF OIL SLIME IN THE INDUSTRIAL OIL AND GAS SECTOR
20-26
-
AUTOMATED DEFINITION OF THE DISCRETE ELEMENTS INTERACTIONS IN WORKSPACE OF EQUIPMENT
27-35
-
TONTOR ZONES MODEL FOR AUTOMATIVE OBJECT MONITORING
36-43
-
THEORETICAL AND EXPERIMENTAL SUBSTANTIATION OF THE EXTRACTION PROCESS WITH THINNING BIMETALLIC TUBULAR ELEMENTS OF DISSIMILAR METALS AND ALLOYS
44-49
-
THE APPLICATION OF MACHINE LEARNING ON THE SENSORS OF SMARTPHONES TO DETECT FALLS IN REAL-TIME
50-55
-
CONVOLUTIONAL NEURAL NETWORKS FOR EARLY COMPUTER DIAGNOSIS OF CHILD DYSPLASIA
56-63
-
CARDIOMETABOLIC RISK PREDICTION IN PATIENTS WITH NON-ALCOHOLIC FATTY LIVER DISEASE COMBINED WITH SUBCLINICAL HYPOTHYROIDISM
64-68
-
LOCAL DIFFERENCE THRESHOLD LEARNING IN FILTERING NORMAL WHITE NOISE
69-73
-
MODELING AND ANALYSIS OF THE CHARACTERISTICS OF MULTICHANNEL AND MULTI-NODE COMPUTER NETWORKS WITH PRIORITY SERVICE
74-77
-
STATISTICAL METHODS FOR EVALUATING EXPERIMENTAL DATA ON THE USE OF MATHEMATICAL COMPETENCIES IN STUDY FOR A RESILIENT ECONOMY
78-85
-
SIMULATION OF THE INFLUENCE OF INVESTMENT AND INNOVATION ACTIVITIES ON ENSURING THE INTERNATIONAL COMPETITIVENESS OF COUNTRIES
86-92
Main Article Content
DOI
Authors
Abstract
With the increasing prevalence of smartphones, they now come equipped with a multitude of sensors such as GPS, microphones, cameras, magnetometers, accelerators, and more, which can simplify our daily lives. When it comes to healthcare, smartphones can become indispensable. The detection of geriatric falls is crucial as even the slightest injury can have fatal consequences. Therefore, we proposed the use of accelerometers in our research to detect falls in the elderly. Our project involved the development of an automated, continuous, and reliable monitoring system that would generate a list of elderly people at risk of falling and present it on a webpage for emergency services. This approach aimed to minimize the long-term impacts and save lives promptly. We started by developing a mobile application and used MATLAB to classify the falls as either "fall" or "not fall." Finally, we created a webpage that would facilitate communication between the mobile application and MATLAB.
