scholarly journals Preliminary Examination of the Accuracy of a Fall Detection Device Embedded into Hearing Instruments

2020 ◽  
Vol 31 (06) ◽  
pp. 393-403
Author(s):  
Justin R. Burwinkel ◽  
Buye Xu ◽  
Jeff Crukley
Keyword(s):  
Repeated Measures ◽  
Inertial Sensors ◽  
Detection System ◽  
Fall Detection ◽  
Analysis Data ◽  
The Body ◽  
Measurement Unit ◽  
Suitable Alternative ◽  
Hearing Instruments ◽  
Personal Emergency Response Systems

Abstract Background Accidental falls are a significant health risk to older adults and patients seen in audiology clinics. Personal emergency response systems are effective in preventing long lies (defined as remaining on the floor or ground for greater than one hour after a fall), but some individuals would prefer to wear less-conspicuous devices than a traditional neck-worn pendant. No previous investigation has compared the accuracy of head-worn fall detection devices with those worn on other parts of the body. In this study, we compared the accuracy of one commonly used fall detection pendant with two variants of a new hearing instrument-based fall detection system. Purpose The purpose of the study was to evaluate the accuracy of detecting falls by using inertial sensors embedded in hearing instruments. Research Design A study with repeated measures for one group. Study Sample Ten young adults served as participants. All participants had normal or corrected-to-normal vision during testing. Individuals were excluded if they had self-reported cardiac disorders, recent concussions, or musculoskeletal conditions. Data Collection and Analysis Data were collected from inertial measurement unit (IMU) sensors, embedded into a binaural set of hearing instruments, during laboratory-based simulations of falls, near-falls, and activities of daily living (ADLs). The detection state of a fall detection pendant was simultaneously recorded during performance of each trial and compared with the outputs of offline hearing instrument firmware emulators. Results One hearing instrument-based fall detection system was more accurate than the fall detection pendant. A second hearing instrument-based fall detection system performed similar to the fall detection pendant. Each of the three fall detection systems investigated were robust against false-positive detections during ADLs. Conclusions Preliminary findings demonstrate that hearing instruments embedded with a fall detection device (FDD) may be a suitable alternative to more traditional forms of FDDs (e.g., pendant, wrist-worn device, etc.) for detecting falls and potentially preventing long lies.

Preliminary Examination of the Accuracy of a Fall-Detection Device Embedded into Hearing Instruments

2019 ◽  
Author(s):  
Justin R. Burwinkel ◽  
Buye Xu ◽  
Jeff Crukley
Keyword(s):  
Repeated Measures ◽  
Detection System ◽  
Fall Detection ◽  
The Body ◽  
Measurement Unit ◽  
Suitable Alternative ◽  
Hearing Instruments ◽  
Response Systems ◽  
Personal Emergency Response Systems ◽  
Emergency Response Systems

Background: Accidental falls are a significant health risk to older adults and patients seen in audiologyclinics. Personal emergency response systems are effective in preventing long lies (defined as remainingon the floor or ground for greater than one hour after a fall), but some individuals would prefer to wear less conspicuousdevices than a traditional neck-worn pendant. No previous investigation has compared theaccuracy of head-worn fall detection devices with those worn on other parts of the body. In this study, wecompared the accuracy of one commonly used fall detection pendant with two variants of a new hearinginstrument–based fall detection system.<br />Purpose: The purpose of the study was to evaluate the accuracy of detecting falls by using inertial sensorsembedded in hearing instruments.<br />Research Design: A study with repeated measures for one group.<br />Study Sample: Ten young adults served as participants. All participants had normal or corrected-to normalvision during testing. Individuals were excluded if they had self-reported cardiac disorders, recentconcussions, or musculoskeletal conditions.<br />Data Collection and Analysis: Data were collected from inertial measurement unit (IMU) sensors, embeddedinto a binaural set of hearing instruments, during laboratory-based simulations of falls, near-falls,and activities of daily living (ADLs). The detection state of a fall detection pendant was simultaneouslyrecorded during performance of each trial and compared with the outputs of offline hearing instrumentfirmware emulators.<br />Results: One hearing instrument–based fall detection system was more accurate than the fall detectionpendant. A second hearing instrument–based fall detection system performed similar to the fall detectionpendant. Each of the three fall detection systems investigated were robust against false-positive detectionsduring ADLs.<br />Conclusions: Preliminary findings demonstrate that hearing instruments embedded with a fall detectiondevice (FDD) may be a suitable alternative to more traditional forms of FDDs (e.g., pendant, wrist-worndevice, etc.) for detecting falls and potentially preventing long lies.<br />

Design and Test of MEMS Attitude Measurement Unit for Fall Detection

2011 ◽  
Vol 483 ◽  
pp. 465-470 ◽  
Author(s):  
Xiao Yan Liu ◽  
Zhao Ying Zhou ◽  
Wei Xiong
Keyword(s):  
Measurement Error ◽  
Data Storage ◽  
Detection System ◽  
Fall Detection ◽  
The Elderly ◽  
Measurement Unit ◽  
Attitude Measurement ◽  
Test Results ◽  
Measurement Units ◽  
Serious Injury

Fall is a risky event in the elderly people’s daily life, it often cause serious injury both in physiology and psychology. A MEMS attitude measurement system is designed for fall detection in real time. This paper presents the design and error test of the attitude measurement unit. Each unit contains orthogonally mounted triads of accelerometers, magnetometers and gyros. With an integrated microcontroller for attitude calculating and flash for data storage, the size of the unit is 32mm×23mm×12mm. An extended Kalman filter based on quaternions is designed for attitude measurement. The digital angle output rate is 100Hz. A new method based on coordinate transformation for attitude measurement error test is introduced, using a single axis turntable and a fixed angle wedge. Theory of the testing method is presented and test experiments are performed. Test results show that attitude measurement error is less than 2°, which meets the requirement of fall detection precision. The fall detection system consists of five attitude measurement units fixed on the human legs and waist.

FALL DETECTION USING THREE WEARABLE TRIAXIAL ACCELEROMETERS AND A DECISION-TREE CLASSIFIER

2014 ◽  
Vol 26 (05) ◽  
pp. 1450059 ◽  
Author(s):  
Kan Luo ◽  
Jianqing Li ◽  
Jianfeng Wu ◽  
Hua Yang ◽  
Gaozhi Xu
Keyword(s):  
Decision Tree ◽  
Detection System ◽  
Human Movement ◽  
Fall Detection ◽  
The Body ◽  
Body Tilt ◽  
Decision Tree Classifier ◽  
Tree Model ◽  
Tree Classifier ◽  
Unintentional Falls

Unintentional falls cause serious health problem and high medical cost, particularly among the elders. Efficient fall detection can ensure fallen subjects with timely rescue, less pain and lower health-care expense. However, the accuracy of the present fall detection system with single accelerometer does not meet the requirement of practical application. In this paper, a fall detection method using three wearable triaxial accelerometers and a decision-tree classifier is proposed. The three triaxial accelerometers are, respectively mounted on the head, the waist and the ankle to capture the acceleration signals of human movement. A Kalman filter is adopted to estimate the body tilt angle. After the features are extracted, the trained decision-tree model is used to predict the fall. The efficiency improvement is evidenced by the scripted and unscripted lateral fall experiments, involving five young healthy volunteers (three males and two females; age: 23.3 ± 1 years). The classification of fall and activities of daily living (ADL) achieve recall, precision and F-value of 93.1%, 95.9%, and 94.5%, respectively, and the system detects all falls during the extended unscripted trials. The experimental results indicate that the complementary movement information coming from three accelerometers can enhance the performance of fall detection. The proposed method is efficient, and it has remarkable improvements in comparison to the method of using one or two accelerometers.

Low Cost Inertial Measurement Unit Application on Sub-Sea Launching: Signal Processing and Trajectory Algorithm

2010 ◽  
Author(s):  
Rodrigo Sauri Lavieri ◽  
Eduardo Aoun Tannuri ◽  
Andre´ L. C. Fujarra ◽  
Celso P. Pesce ◽  
Diego Cascelli Correˆa
Keyword(s):  
Automobile Industry ◽  
Inertial Measurement Unit ◽  
Inertial Sensors ◽  
The Body ◽  
Measurement Unit ◽  
Final Position ◽  
Test Procedures ◽  
Positioning Systems ◽  
Inertial Measurement ◽  
Offshore Industry

Many situations in the Offshore Industry require equipment to be launched to the sea floor, becoming important to measure or to estimate their final position and/or to determine the complete trajectory. Some examples are the installation of anchorage devices, manifolds or production line supports. The main problem associated with the estimation of the position and the trajectory of the equipment is related to the fact that, systems such as GPSs and magnetometers cannot be used in subsea conditions. Gyrocompass and precise inertial sensors can be used, but they are expensive equipments and there is the risk of damaging during the launch process. The solution is to develop cost-effective inertial positioning systems that reach the operational requirements related to measuring accuracy. These equipments are based on MEMS (Micro-Electrical Mechanical Systems) inertial sensors that are relatively cheap. However, without the proper care, the signals obtained by these equipments present large levels of noise, bias and poor repeatability. The aim is to show a sequence of test procedures, treatment and processing of signals that leads one to know the position, attitude and trajectory of a submarine device. Furthermore, it allows the quantification of errors and, eventually, their sources. A commercial IMU (Inertial Measurement Unit) was chosen as a case study. It is equipped with MEMS sensors, usually adopted by the automobile industry. Tests with IMU were carried out intending to find the sensors scale factors, their bias and temperature sensitivity. Thereafter, the data were processed by two distinct algorithms. The first one is a simple algorithm that computes the attitude, azimuth at the final position and calculates the terminal velocity during the launch. The second one integrates the signal along all the movement by using quaternions algebra, resulting in the complete trajectory of the body. Discussions about the accuracy, applicability and limitations of each method are presented.

scholarly journals Innovative Head-Mounted System Based on Inertial Sensors and Magnetometer for Detecting Falling Movements

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5774
Author(s):  
Chih-Lung Lin ◽  
Wen-Ching Chiu ◽  
Ting-Ching Chu ◽  
Yuan-Hao Ho ◽  
Fu-Hsing Chen ◽  
...  
Keyword(s):  
Activities Of Daily Living ◽  
Daily Living ◽  
Inertial Sensors ◽  
Daily Life ◽  
Detection System ◽  
Fall Detection ◽  
Experimental Results ◽  
Triaxial Accelerometer ◽  
Timely Manner

This work presents a fall detection system that is worn on the head, where the acceleration and posture are stable such that everyday movement can be identified without disturbing the wearer. Falling movements are recognized by comparing the acceleration and orientation of a wearer’s head using prespecified thresholds. The proposed system consists of a triaxial accelerometer, gyroscope, and magnetometer; as such, a Madgwick’s filter is adopted to improve the accuracy of the estimation of orientation. Moreover, with its integrated Wi-Fi module, the proposed system can notify an emergency contact in a timely manner to provide help for the falling person. Based on experimental results concerning falling movements and activities of daily living, the proposed system achieved a sensitivity of 96.67% in fall detection, with a specificity of 98.27%, and, therefore, is suitable for detecting falling movements in daily life.

WeMos IoT Controller-Based Low-Cost Fall Detection System for Elderly Users

2021 ◽  
Vol 50 ◽  
pp. 59-72
Author(s):  
Mohammed Faeik Ruzaij Al-Okby ◽  
Kerstin Thurow
Keyword(s):  
False Positive ◽  
Detection System ◽  
Low Cost ◽  
False Negative ◽  
Lithium Ion ◽  
Fall Detection ◽  
The Elderly ◽  
The Body ◽  
Detection Systems ◽  
Alarm Message

Fall detection systems for the elderly are very important to protect this type of users. The early detection of the fall of the elderly has a major impact on saving their lives and avoiding the deterioration of the negative medical effects resulting from the effect of the patient falling on a hard surface. One of the constraints in fall detection systems are false-negative errors (no fall detection) or false-positive errors (sending a false warning without real fall accident). These errors have to be reduced significantly. In this paper, an innovative method to reduce fall detection system errors is proposed. The system consists of two orientation detection sensors to track the body orientation instead of using a single sensor in the previous systems which enhances the system accuracy and reduces the false-negative and false-positive errors. The system uses a small size IoT-based controller to process the sensor's information and make the alarm decision based on specific thresholds. The output alarm of the system includes an email sent to the caregivers via the embedded Wi-Fi ESP8266 module as well as an SMS message to the caregivers’ phones via GSM modules to ensure that the alarm message arrives in the absence of internet coverage for the patient or the caregiver. The system is powered by a small lithium-Ion battery. All sensors and modules of the system are combined in a small rubber box that can be fixed in a waist belt or the chest rejoin of the user body. Several tests have been made in different procedures. The tests revealed that the new approach improves the accuracy of the system and reduces the possibility of triggering wrong alarms.

Speech Perception in Noise Using Directional Microphones in Open-Canal Hearing Aids

2008 ◽  
Vol 19 (07) ◽  
pp. 571-578 ◽  
Author(s):  
Emily J. Klemp ◽  
Sumitrajit Dhar
Keyword(s):  
Data Collection ◽  
Hearing Aids ◽  
Repeated Measures ◽  
Analysis Data ◽  
Impaired Hearing ◽  
Directional Microphones ◽  
Hearing In Noise ◽  
Hearing Instruments ◽  
Data Collection And Analysis ◽  
Bilateral Sensorineural Hearing Loss

Background: Individuals with impaired hearing find it difficult to understand speech in the presence of background noise—a problem addressed effectively by directional microphones. As open-canal fittings have become increasingly popular in the recent past, so has the debate about the effective directional benefit available from these devices. Purpose: This study investigates the benefit of directional microphones in two commercially available open-canal behind-the-ear hearing aids using the Hearing in Noise Test (HINT). Study Sample: Sixteen individuals, between 50 and 85 year of age, with high-frequency bilateral sensorineural hearing loss and no previous hearing aid experience participated in this study. Data Collection and Analysis: Data Collection and Analysis: Individuals were asked to repeat sentences (presented at 0° azimuth) in the presence of a diffuse-field uncorrelated broadband speech-shaped noise. HINT performance was compared across hearing instruments and conditions using a linear model with repeated measures. Results: There was a directional advantage of 2.6 dB as compared to the unaided condition. Average performance was worse in the omnidirectional mode as compared to the unaided condition. Conclusions: These results suggest that directional signal processing should not be precluded in open-canal instruments for listening in noisy environments.

scholarly journals Pedestrian Navigation Method Based on Machine Learning and Gait Feature Assistance

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1530 ◽  
Author(s):  
Zijun Zhou ◽  
Shuqin Yang ◽  
Zhisen Ni ◽  
Weixing Qian ◽  
Cuihong Gu ◽  
...  
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Sensors ◽  
Inertial Navigation ◽  
The Body ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Pedestrian Navigation ◽  
Gait Feature ◽  
Navigation Method

In recent years, as the mechanical structure of humanoid robots increasingly resembles the human form, research on pedestrian navigation technology has become of great significance for the development of humanoid robot navigation systems. To solve the problem that the wearable inertial navigation system based on micro-inertial measurement units (MIMUs) installed on feet cannot effectively realize its positioning function when the body movement is too drastic to be measured correctly by commercial grade inertial sensors, a pedestrian navigation method based on construction of a virtual inertial measurement unit (VIMU) and gait feature assistance is proposed. The inertial data from different positions of pedestrians’ lower limbs are collected synchronously via actual IMUs as training samples. The nonlinear mapping relationship between inertial information from the human foot and leg is established by a visual geometry group-long short term memory (VGG-LSTM) neural network model, based on which the foot VIMU and virtual inertial navigation system (VINS) are constructed. The VINS experimental results show that, combined with zero-velocity update (ZUPT), the integrated method of error modification proposed in this paper can effectively reduce the accumulation of positioning errors in situations where the gait type exceeds the measurement range of the inertial sensors. The positioning performance of the proposed method is more accurate and stable in complex gait types than that merely using ZUPT.

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