Evaluating the Accuracy of Step Tracking and Fall Detection in the Starkey Livio Artificial Intelligence Hearing Aids: A Pilot Study

2020 ◽  
pp. 1-8
Author(s):  
Mohamed Rahme ◽  
Paula Folkeard ◽  
Susan Scollie
Keyword(s):  
Artificial Intelligence ◽  
Hearing Aids ◽  
Real World ◽  
Daily Living ◽  
Fall Detection ◽  
Step Count ◽  
Alert System ◽  
The Real ◽  
Secondary Purpose ◽  
Treadmill Protocol

Purpose The primary purpose of this study was to examine the efficacy and the effectiveness of Starkey Livio Artificial Intelligence hearing aids in tracking step count. A secondary purpose was to investigate the accuracy of the fall detection and alert system of Livio hearing aids in detecting fall maneuvers. Method A participant wore Binaural Starkey Livio receiver-in-the-canal style hearing aids, a Sportline pedometer, and a Fitbit Charge 3 concurrently during both real-world and treadmill walking conditions. The real-world condition was conducted over a 5-day period. Step count for the treadmill protocol was assessed at six different treadmill speeds (2 mph, 2.5 mph, 3 mph, 3.5 mph, 4 mph, 4.5 mph, and 5 mph). The fall detection and alert system were assessed through falling maneuvers of activities of daily living. Results In the real-world condition, Livio, Sportline, and Fitbit recorded steps within 1 SD of each other. In addition, Livio recorded the most accurate steps compared to actual physical steps taken. In the treadmill condition, Livio recorded the least number of steps across all walking paces compared to the rest of the devices. Also, Livio hearing aids detected majority of the engaged falling maneuvers. Conclusions The Livio was found to be feasible, consistent, and sensitive in detecting steps and falls. Further research of higher sample size and recruitment of individuals with hearing loss are suggested.

scholarly journals Re-Enactment as a Method to Reproduce Real-World Fall Events Using Inertial Sensor Data: Development and Usability Study

10.2196/13961 ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. e13961
Author(s):  
Kim Sarah Sczuka ◽  
Lars Schwickert ◽  
Clemens Becker ◽  
Jochen Klenk
Keyword(s):  
Real World ◽  
Independent Living ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Center Of Mass ◽  
Fall Detection ◽  
Video Data ◽  
Sensor Data ◽  
Movement Behavior ◽  
The Real

Background Falls are a common health problem, which in the worst cases can lead to death. To develop reliable fall detection algorithms as well as suitable prevention interventions, it is important to understand circumstances and characteristics of real-world fall events. Although falls are common, they are seldom observed, and reports are often biased. Wearable inertial sensors provide an objective approach to capture real-world fall signals. However, it is difficult to directly derive visualization and interpretation of body movements from the fall signals, and corresponding video data is rarely available. Objective The re-enactment method uses available information from inertial sensors to simulate fall events, replicate the data, validate the simulation, and thereby enable a more precise description of the fall event. The aim of this paper is to describe this method and demonstrate the validity of the re-enactment approach. Methods Real-world fall data, measured by inertial sensors attached to the lower back, were selected from the Fall Repository for the Design of Smart and Self-Adaptive Environments Prolonging Independent Living (FARSEEING) database. We focused on well-described fall events such as stumbling to be re-enacted under safe conditions in a laboratory setting. For the purposes of exemplification, we selected the acceleration signal of one fall event to establish a detailed simulation protocol based on identified postures and trunk movement sequences. The subsequent re-enactment experiments were recorded with comparable inertial sensor configurations as well as synchronized video cameras to analyze the movement behavior in detail. The re-enacted sensor signals were then compared with the real-world signals to adapt the protocol and repeat the re-enactment method if necessary. The similarity between the simulated and the real-world fall signals was analyzed with a dynamic time warping algorithm, which enables the comparison of two temporal sequences varying in speed and timing. Results A fall example from the FARSEEING database was used to show the feasibility of producing a similar sensor signal with the re-enactment method. Although fall events were heterogeneous concerning chronological sequence and curve progression, it was possible to reproduce a good approximation of the motion of a person’s center of mass during fall events based on the available sensor information. Conclusions Re-enactment is a promising method to understand and visualize the biomechanics of inertial sensor-recorded real-world falls when performed in a suitable setup, especially if video data is not available.

scholarly journals City brain: practice of large‐scale artificial intelligence in the real world

2019 ◽  
Vol 1 (1) ◽  
pp. 28-37 ◽  
Author(s):  
Jianfeng Zhang ◽  
Xian‐Sheng Hua ◽  
Jianqiang Huang ◽  
Xu Shen ◽  
Jingyuan Chen ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Real World ◽  
Large Scale ◽  
The Real

Artificial Intelligence Screening for Diabetic Retinopathy: the Real-World Emerging Application

2019 ◽  
Vol 19 (9) ◽  
Author(s):  
Valentina Bellemo ◽  
Gilbert Lim ◽  
Tyler Hyungtaek Rim ◽  
Gavin S. W. Tan ◽  
Carol Y. Cheung ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Diabetic Retinopathy ◽  
Real World ◽  
The Real

Embodying Cognition

2010 ◽  
pp. 344-366 ◽  
Author(s):  
David Casacuberta ◽  
Saray Ayala ◽  
Jordi Vallverdú
Keyword(s):  
Artificial Intelligence ◽  
Real World ◽  
The Real ◽  
Specific Reading ◽  
Natural Forms ◽  
Lego Mindstorms ◽  
The Mind ◽  
Embodied Agent ◽  
Reasonable Model

After several decades of success in different areas and numerous effective applications, algorithmic Artificial Intelligence has revealed its limitations. If in our quest for artificial intelligence we want to understand natural forms of intelligence, we need to shift/move from platform-free algorithms to embodied and embedded agents. Under the embodied perspective, intelligence is not so much a matter of algorithms, but of the continuous interactions of an embodied agent with the real world. In this paper we adhere to a specific reading of the embodied view usually known as enactivism, to argue that 1) It is a more reasonable model of how the mind really works; 2) It has both theoretical and empirical benefits for Artificial Intelligence and 3) Can be easily implemented in simple robotic sets like Lego Mindstorms (TM). In particular, we will explore the computational role that morphology can play in artificial systems. We will illustrate our ideas presenting several Lego Mindstorms robots where morphology is critical for the robot’s behaviour.

Special Issue on Integrated Knowledge on Innovative Robot Mechanisms

2018 ◽  
Vol 30 (6) ◽  
pp. 845-845
Author(s):  
Naoyuki Takesue ◽  
Koichi Koganezawa ◽  
Kenjiro Tadakuma
Keyword(s):  
Artificial Intelligence ◽  
Real World ◽  
Computer Control ◽  
Computer Processing ◽  
Knowledge System ◽  
Mechanical Work ◽  
The Other ◽  
Special Issue ◽  
The Real ◽  
Integrated Knowledge

A robot is a system integrated with many elements such as actuators, sensors, computers, and mechanical components. Currently, progress in the field of artificial intelligence induced by tremendous improvements in computer processing capabilities has enabled robots to behave in a more sophisticated manner, which is drawing considerable attention. On the other hand, the mechanism that directly produces robot movements and mechanical work sometimes brings out some competencies that cannot be provided solely by computer control that relies on sensor feedback. This special issue on “Integrated Knowledge on Innovative Robot Mechanisms” aims to introduce a knowledge system for robot mechanisms that bring forth useful and innovative functions and values. The editors hope that the studies discussed in this special issue will help in the realization and further improvement of the mechanical functions of robots in the real world.

scholarly journals Adversarial Examples in Physical World

2021 ◽  
Author(s):  
Jiakai Wang
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Potential Risk ◽  
Real World ◽  
Deep Neural Networks ◽  
Physical World ◽  
The Real ◽  
Wide Range ◽  
Adversarial Examples ◽  
Ai Safety

Although deep neural networks (DNNs) have already made fairly high achievements and a very wide range of impact, their vulnerability attracts lots of interest of researchers towards related studies about artificial intelligence (AI) safety and robustness this year. A series of works reveals that the current DNNs are always misled by elaborately designed adversarial examples. And unfortunately, this peculiarity also affects real-world AI applications and places them at potential risk. we are more interested in physical attacks due to their implementability in the real world. The study of physical attacks can effectively promote the application of AI techniques, which is of great significance to the security development of AI.

scholarly journals The Technical Buzzword: Artificial Intelligence

2021 ◽  
Vol 1 (4) ◽  
pp. 1-3
Author(s):  
Banya Arabi Sahoo ◽  
Keyword(s):  
Artificial Intelligence ◽  
Human Brain ◽  
Real World ◽  
Human Being ◽  
Science And Engineering ◽  
The Real ◽  
Advantages And Disadvantages ◽  
Real World Problem ◽  
John Mccarthy ◽  
The World

AI is the incredibly exciting technique to the world. According to John McCarthy it is “The science and engineering of making intelligent machine, especially intelligent computers”. AI is the way of creating extraordinary powerful machine which is similar as human being. The AI is being accomplished by studying how human brain think, how they learn, decide, work, solving the real world problem and after that verify the outcomes and studying it. Primarily you can learn here what AI is and how it works, its types, its history, its agents, its applications, its advantages and disadvantages.

scholarly journals Artificial Intelligence and the Problem of Control

2021 ◽  
pp. 19-24
Author(s):  
Stuart Russell
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Standard Model ◽  
Real World ◽  
New Model ◽  
The Real ◽  
Ability To Act ◽  
The Standard Model ◽  
Philosophy And Economics

AbstractA long tradition in philosophy and economics equates intelligence with the ability to act rationally—that is, to choose actions that can be expected to achieve one’s objectives. This framework is so pervasive within AI that it would be reasonable to call it the standard model. A great deal of progress on reasoning, planning, and decision-making, as well as perception and learning, has occurred within the standard model. Unfortunately, the standard model is unworkable as a foundation for further progress because it is seldom possible to specify objectives completely and correctly in the real world. The chapter proposes a new model for AI development in which the machine’s uncertainty about the true objective leads to qualitatively new modes of behavior that are more robust, controllable, and deferential to humans.

scholarly journals Methods for the Real-World Evaluation of Fall Detection Technology: A Scoping Review

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2060 ◽  
Author(s):  
Robert Broadley ◽  
Jochen Klenk ◽  
Sibylle Thies ◽  
Laurence Kenney ◽  
Malcolm Granat
Keyword(s):  
Scoping Review ◽  
Real World ◽  
Fall Detection ◽  
The Real ◽  
Detection Technology

Mind in the World

1970 ◽  
Vol 7 (1) ◽  
pp. 193-204
Author(s):  
Jan Regner
Keyword(s):  
Artificial Intelligence ◽  
Real World ◽  
Philosophical Problem ◽  
Chinese Room ◽  
The Real ◽  
The World

As the title of my article can indicate, the primary aim of this „brief introduction" is to present the concept of intentionality of one of the world's leading philosophers - John R. Searle. Searle is known for his severe criticism of the dominant traditions in the study of mind, both materialist and dualist, and we may also recall his familiar argument called „the Chinese Room" against theories of „artificial intelligence". The concept of intentionality was founded when philosophers attempted to describe and solve the philosophical problem of specific „quasi-relations" between consciousness and objects and the direction of our mind or language to the real world. I am referring to situations in which we say for instance: „A thinks about p", "B maintains that g", „X asks question if y" and so on.

Sign in / Sign up

Export Citation Format

Share Document