Inattentive Driving Detection Using Body-Worn Sensors: Feasibility Study

This study aims to build a system for detecting a driver’s internal state using body-worn sensors. Our system is intended to detect inattentive driving that occurs during long-term driving on a monotonous road, such as a high-way road. The inattentive state of a driver in this study is an absent-minded state caused by a decrease in driver vigilance levels due to fatigue or drowsiness. However, it is difficult to clearly define these inattentive states because it is difficult for the driver to recognize when they fall into an absent-minded state. To address this problem and achieve our goal, we have proposed a detection algorithm for inattentive driving that not only uses a heart rate sensor, but also uses body-worn inertial sensors, which have the potential to detect driver behavior more accurately and at a much lower cost. The proposed method combines three detection models: body movement, drowsiness, and inattention detection, based on an anomaly detection algorithm. Furthermore, we have verified the accuracy of the algorithm with the experimental data for five participants that were measured in long-term and monotonous driving scenarios by using a driving simulator. The results indicate that our approach can detect both the inattentive and drowsiness states of drivers using signals from both the heart rate sensor and accelerometers placed on wrists.

Sleep-Wake Pattern, Sleep Quality and Daytime Status in Fixed Day-Shift Hospital Workers

Objectives: Sleep issues are more prevalent in healthcare workers compared to workers in other industries. This study investigated sleep-wake pattern, sleep quality, and daytime status in hospital workers using a Galaxy Watch3 (GW3), a wrist-worn device that uses an accelerometer and heart rate sensor to distinguish sleep and wakefulness.Methods: Multiple sleep parameters including total sleep time (TST) were obtained using a GW3. The Epworth sleepiness scale (ESS), insomnia severity index (ISI), Pittsburgh sleep quality index (PSQI), and bedtime procrastination scale (BPS) were used to assess participants’ status.Results: A total of 70 daytime hospital workers (male, 45.7%; mean age, 35.66±7.79 yr) participated in the monitoring of their sleep-wake patterns for 30 consecutive days. Participants had a mean ESS of 8.14±3.62, ISI of 6.13±3.83, and PSQI of 4.86±2.14. The mean TST was 5.75±0.74 hr (range: 3.42–6.88) during workdays and 5.92±0.92 hr (range: 2.87–8.25) during free days. Chronotype (mid-sleep on freedays corrected for sleep debt accumulated over the work week) was 3.60±1.03 clock hr (range: 1.84–6.69). BPS was negatively correlated with age (rho=-0.27, p=0.022), TST of workdays (rho=-0.53, p<0.001), and TST of free days (rho=-0.43, p<0.001). A higher BPS was associated with larger social jetlag (rho=0.28, p=0.018) and later chronotype (rho=0.41, p<0.001).Conclusions: In this study, 91.5% of daytime hospital workers suffered from chronic sleep insufficiency (<7 hr during both workdays and free days) although their daytime sleepiness or subjective sleep were not poor. Individuals with a later chronotype had poorer sleep quality and worse sleep procrastination behavior.

Validity of the Wrist-Worn Polar Vantage V2 to Measure Heart Rate and Heart Rate Variability at Rest

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11340 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (bias −0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (bias 0.20 ms, p < 0.001) and nocturnal recordings (bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.

Design and Simulation of the Two-Axis Micromachined Angular Rate Sensor

Micromechanical inertia sensors - accelerometers, gyroscopes, multisensor modules and systems based on them - are widely used in navigation, for compensation of other instruments (accelerometers, inclinometers) or stabilization (gyroscopes). The paper presents the designed construction of a MEMS angular rate sensor with two sensitivity axes, topology of gyroscope is presented; modal and static analysis is performed using ANSYS CAD; simulation results of micromechanical gyroscope operation under the action of angular velocities using VHDL-AMS are presented.

Microcontroller Based Portable Incubator Monitoring Tool with Short Message Service (SMS) notifications

The aim of this research was applied a microcontroller, temperature sensor, weight sensor, heart rate sensor and GSM module to monitoring and notification of the condition of premature babies in portable incubators. The hardware used consists of a DS18B20 sensor, Load Cell, Pulse Heart Rate Sensor, Buzzer, LCD and SIM800L Module. The results showed the Pulse sensor and DS18B20 sensor could measure and detect the baby’s heart rate and baby temperature. The result was on the LCD with an average error of 4.354% for heartrate and 1.437% for temperature. The loadcell sensor can detect weight with an error of 2.16%. The duration of sending SMS to Smartphone is 8s for each delivery. SMS was sent if the baby weak and critical condition.

Alarm warning dan rem otomatis berbasis detak jantung pada olahraga bersepeda

Jantung merupakan organ vital pada tubuh manusia. Oleh karena itu, penting dalam memelihara kesehatan jantung. Salah satunya melalui pelatihan berbasis detak jantung, yaitu menjaga detak jantung dalam kisaran yang ditetapkan. Salah satu pengaplikasiannya adalah olahraga bersepeda, namun tidak jarang pesepeda melebihi target maksimal saat bersepeda, sehingga hal tersebut menyalahi aturan dalam pelatihan. Prinsip kerja alat ini adalah mengaktifkan alarm warning jika detak jantung pengguna melebihi target maksimal saat latihan dan mengaktifkan rem otomatis ketika pengguna menghiraukan alarm warning. Target latihan diperoleh dari perhitungan umur, maximal heart rate (MHR), Rest Heart Rate (RHR), dan riwayat latihan. Penelitian ini menggunakan grove heart rate sensor sebagai sensor detak jantung dengan mikrokontroler Arduino MEGA. Proses pengambilan maupun penyimpanan data pada database dilakukan oleh NodeMCU. Motor DC 12V digunakan sebagai penarik rem dengan driver motor sebagai pengatur arah dan putaran motor. Berdasarkan hasil pengujian diperoleh bahwa data detak jantung peserta latihan tersimpan dalam database sistem, alarm warning bekerja(buzzer on) jika detak jantung peserta diatas 135 bpm, dan rem otomatis bekerja pada saat detak jantung peserta latihan diatas 135 bpm dengan berubahnya panjang tali rem dari 15 cm menjadi 12 cm. The heart is a vital organ in the human body. Therefore, it is important in maintaining heart health. One of them is through heart rate-based training, which is keeping the heart rate within a specified range. One of its applications is cycling, but it is not uncommon for cyclists to exceed the maximum target when cycling, so that this violates the rules in training. The working principle of this tool is to activate an alarm warning if the user's heart rate exceeds the maximum target during training and activate the automatic brake when the user ignores the alarm warning. Training targets are obtained from the calculation of age, maximal heart rate (MHR), Rest Heart Rate (RHR), and training history. This study uses a grove heart rate sensor as a heart rate sensor with an Arduino MEGA microcontroller. The process of retrieving and storing data in the database is carried out by NodeMCU. DC 12V motor is used as a brake puller with the motor driver to control the direction and rotation of the motor. Base on the test result, it is found that the participant’s heart rate data is stored in the database system, the alarm warning work (buzzer on)if the participant’s herat rate is above 135 bpm, and the brakes automatically work when the participant’s herat rate is above 135 bpm by changing the length of the brake rope from 15cm to 12 cm.

Modelling Human Activity using Smartphone Data

Background: Over time, multichannel time series data were utilized for the purpose of modeling human activity. Instruments such as an accelerometer and gyroscope which had sensors embedded in them, recorded sensor data which were then utilized to record 6-axes, single dimensional convolution for the purpose of formulating a deep CNN. The resultant network achieved 94.79% activity recognition accuracy on raw sensor data, and 95.57% accuracy when Fast Fourier Transform (FFT) knowledge was added to the sensor data. Objective: This study helps to achieve an orderly report of daily Human activities for the overall balanced lifestyle of a healthy human being. Methods: Interfacing is done using Arduino Uno, Raspberry-Pi 3, heart rate sensor and accelerometer ADXL345 to generate real time values of day-to-day human activities such as walking, sleeping, climbing upstairs/downstairs and so on. Initially, the heart pulse of our four tested individuals is recorded and tabulated to depict and draw conclusions all the way from “Low BP” to “Heavy Exercise”. The convolution neural network is initially trained with an online human activity dataset and tested using our real time generated values which are sent to the MAC OS using a Bluetooth interface. Results: We obtain graphical representations of the amount of each activity performed by the test set of individuals, and in turn conclusions which suggest increase or decrease in the consistency of certain activities to the users, depicted through our developed iOS application, “Fitnesse”. Conclusion: The result of this works is used to improve the daily health routines and the overall lifestyle of distressed patients.

A prelude to wearable technology for the measurement and restoration of core body temperature and heart rate in athletes suffering from hypothermia

An individual who is in good physical health tends to exhibit an internal core temperature of 37°C and a heart rate of 60–100 beats per minute. Increase in the temperature of the surrounding environment can serve as the basis for the onset of the condition of Hypothermia. Hypothermia acts as one of the most significant barriers being faced by winter athletes and starts initially with an increase in the heart and breathing rate. However, if the condition persists it can lead to reduction in the heart and breathing rate and ultimately results in cardiac failure. Although, jackets are commercially available, they tend to operate manually and furthermore, do not serve the primary purpose of counteracting the condition of hypothermia, particularly experienced by athletes taking part in winter sports. The objective of this study is to design a heating jacket that enables effective counteraction of the condition of Hypothermia. It enables precise measurement of the of core body temperature with the aid of a pyroelectric sensor. Along with this, a pulse rate sensor for detecting the accurate heart rate has been incorporated on the index finger. Five heating pads would get activated to attain optimal temperature, in case the core body temperature of <37°C is detected. If the condition of hypothermia advances to the moderate stage, two additional heating pads will get activated and provide extra warmth to attain normal heart rate along with core body temperature. Overall, this wearable technology serves as a definitive solution to counteract the condition of hypothermia only when the internal parameters exhibit that you actually have it. The results of the study exhibited that this prototype can be utilized for detecting and treating the condition of Hypothermia.

Cognitive Support Tools for a Pre-Performance Routine in a Darts Game

This paper describes two types of a cognitive support tool for a pre-performance routine (PPR) in darts game. PPRs entail the performance of determined motions before an action and are often executed in sports for the purpose of removing stress or raising concentration. The concentration-stabilizing phenomenon was discovered by the previous research and it determined that the phenomenon appears more conspicuous in the case of experts and PPRs. A tool using a simple brainwaves sensor has been designed and shows us the current status of concentration and notifies us of the concentration-stabilizing phenomenon on a tablet computer. Another tool has been developed on a smart watch with a heart rate sensor. The smart watch indicated heartbeat as a “beep” sound to a user. It was designed based on a result that indicated that darts game scores tend to improve by throwing immediately after a heartbeat. The effectiveness of the tools was verified in several experiments.

Cognitive Support Tools for Pre-Performance Routine in Darts Game

This paper describes two types of a cognitive support tool for a pre-performance routine (PPR) in darts game. PPRs entail the performance of determined motions before an action and are often executed in sports for the purpose of removing stress or raising concentration. The concentration-stabilizing phenomenon was discovered by the previous research and it determined that the phenomenon appears more conspicuous in the case of experts and PPRs. A tool using a simple brainwaves sensor has been designed and shows us the current status of concentration and notifies us of the concentration-stabilizing phenomenon on a tablet computer. Another tool has been developed on a smart watch with a heart rate sensor. The smart watch indicated heartbeat as a “beep” sound to a user. It was designed based on a result that indicated that darts game scores tend to improve by throwing immediately after a heartbeat. The effectiveness of the tools was verified in several experiments.