Exercise Measurement using a Built-in Camera in a Mobile Device(AsianCHI2020)
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Exercise Measurement using a Built-in Camera in a Mobile Device, Asian CHI Symposium 2020, April 25, 2020
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![02 Recognition Principle
・ 30 feature points are extracted by using the Single Face Tracker for Unity Plugin [3].
・The system uses 62 parameters: 30 feature points × 2 (x and y) + two distances.
・Obtained data is divided into every frames.
・After removing a trend, it applies Fast Fourier
Transform (FFT) and uses half of all dimensions’
frequency components for making
a Support Vector Machine’s (SVM’s) classifier.
Exercise Measurement
using a Built-in Camera
in a Mobile Device
Kaho Kato
Keio University
Chengshuo Xia
Keio University
Yuta Sugiura
Keio University
01 Introduction
Background Problem
・Exercise is important to keep our health.
・Our motivation for exercise can be improved
by using the systems that can measure
and record our exercises automatically.
・Many studies have been proposed that can
measure exercises automatically by cameras.
・In most measurement methods, users need
a large space to capture a whole body within
an angle of view of a camera.
・Inaba[1] proposed an exercise measurement
method using the human face’s feature
points got via mobile devices.
・We investigated what kind of movements
can be identified by the face’s feature points.
Approach
[3]ULSeeInc.2017.SingleFaceTrackerPlugin(LiteVersion-30FaceTrackingPoints)-AssetStore.(2017).(Accessedon01/13/2020).
Contact: kaho_0128@keio.jp
03 Recording Application
・An application based on Unity is developed to record and uses
a built-in camera video on a mobile device.
・During excising, it tracks 30 feature points on the face.
・When a user completes, it writes data into CSV files.
04 Kind of Exercise
・9 kinds of exercise were defined, referring to the research of Hashizume[2].
・Standing exercises: To train the lower half of the body.
A user can do anywhere.
・On the floor exercises: To train the trunk of the body.
They need a specific place.
・Limitations
The system- needs a high frame rate to get smooth data.
- is vulnerable to darkness or shielding.
- needs a user to keep the face putting within an angle
of a camera view.
・Future Works
We will - investigate how many feature points are suitable for
classification to reduce calculate costs.
- gather more data to derive a more accurate model.
05 Evaluation 06 Limitations & Future Works
・Participants:
10 people.
・Order of exercises:
Randomly.
・Learning data:
Leave One Participant
Out cross-validation
・The average accuracy:
About 89.4%.
[1]KonomiInabaetal.2019.Tablet
ApplicationforHeel-raiseTraining
byDetectingFaceMovement.In
EntertainmentComputing2019,Vol.
2019.393–397.
・Walking
・Jogging
・High knee raise exercise
・Heel raise and lower exercise
・Squat exercise
・No exercise(Standing straight)
・Sit-ups exercise
・Push-ups exercise
・Back extension exercise
Standing On the floor
[2]HiroshiHashizumeetal.2014.
Developmentand evaluationofavideo
exerciseprogramforlocomotive
syndromeintheelderly.Modern
Rheumatology24,2(2014),250–257.](https://image.slidesharecdn.com/asianchi20katov3-200924073040/85/Exercise-Measurement-using-a-Built-in-Camera-in-a-Mobile-Device-AsianCHI2020-1-320.jpg)
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The document discusses method study, which aims to improve work processes and reduce costs. It describes the objectives and typical procedure of method study, which includes selecting a job to study, recording details, examining the method critically, developing an improved method, installing it, and maintaining the new standard. The document also explains micro-motion study and memo-motion study as techniques for recording and analyzing activities in detail or at a macro level to identify unnecessary motions and establish more efficient methods. The key difference is that micro-motion studies operations at a finer level of detail using filmed footage, while memo-motion uses time-lapse photography to study overall processes.
A Study of Wearable Accelerometers Layout for Human Activity Recognition(Asia...
The document summarizes a study on optimizing the placement of wearable accelerometers for human activity recognition. It describes experimenting with different numbers and positions of sensors, using a particle swarm optimization algorithm to determine optimal combinations that maximize classification accuracy. The results show 2 sensors provide good recognition, while more sensors particularly help with transitional activities, and upper body positions like chest, waist and shoulders perform best. Placements are evaluated for static, dynamic and transitional daily living activities.
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An eye gaze detection using low resolution web camera in desktop environment
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IRJET- Automated Attendance System using Face Recognition
IRJET- Automated Attendance System using Face Recognition
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Yoga Pose Detection and Correction using Posenet and KNN
Human pose detection using machine learning by Grandel
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IRJET- Survey on Face Recognition using Biometrics
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Developing Image Processing System for Classification of Indian Multispectral...
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IRJET - Facial Recognition based Attendance System with LBPH
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Human Movement Recognition Using Internal Sensors of a Smartphone-based HMD (...
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IRJET-Vision Based Occupant Detection in Unattended Vehicle
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A Study of Wearable Accelerometers Layout for Human Activity Recognition(Asia...
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TataPixel: 畳の異方性を利用した切り替え可能なディスプレイの提案
本研究では、畳を利用した新しいディスプレイであるTataPixelを提案しています。畳の表面に織り込まれたイグサは、その繊維の方向によって光の反射具合が異なります。そのため，畳を回転させることで視覚的な色の変化が生じます。これを畳の異方性と呼びます。TataPixel は1 つの円状の畳を1 ピクセルとし、これらを並べることで様々な画像や動画を表現することができます。システムはユーザが画像を入力するソフトウェアと畳を回転させるハードウェアから構成され，容易にTataPixel を操作することができます。
EarAuthCam: Personal Identification and Authentication Method Using Ear Image...
Earphones are now used for longer hours than before with the advancement in wireless technology and miniaturization. In addition, the application of earphones has become more diverse, and opportunities to access highly confidential information through them have increased. We propose a method comprising a hearable device equipped with a small camera for user authentication from ear images. This method improves the security of the hearable device. Ear images are first captured with the camera. The ear regions in the images are then extracted using a mask region-based convolutional neural network. Finally, the user is identified using histograms of oriented gradient features and a support vector machine (SVM). Our method was able to identify 18 participants with an accuracy of 84.1%. Users are authenticated through unsupervised anomaly detection using an autoencoder with an error rate of 8.36%. This method facilitates hands- and eye-free operations without requiring any explicit authentication action by the user.
プレイマットのパターン生成支援ツールの評価
クッション性の高い素材でできたプレイマットは乳幼児の転倒による怪我を防止するため，家庭内やプレイルームなどの幅広い環境で使用される．また，周辺がパズルのような形状となっているため，マットを配置したいスペースに合わせて自由にサイズや形状を変えることができる．本研究は異なる色のプレイマットを用いて動物や数字，文字などのパターンを描くためのデザインインタフェースを提案する．これにより子どもたちが楽しみながら絵を描くことが可能になり，プレイマットに乳幼児の安全の確保だけではなく，床にデザインを表示するツールとしての用途を与える．さらに，マットを配置したいスペースに必要なマット数を直感的に把握することができ，育児の負担軽減が期待できる．
プレイマットのパターン生成支援ツール
クッション性の高い素材でできたプレイマットは乳幼児の転倒による怪我を防止するため, 家庭内やプレイルームなどの幅広い環境で使用される．また，周辺がパズルのような形状となっているため，マットを配置したいスペースに合わせて自由にサイズや形状を変えることができる．本システムは異なる色のプレイマットを用いてパターンを描くためのアプリケーションを提案する．これにより子どもたちが楽しみながら絵を描くことが可能になり，プレイマットに乳幼児の安全の確保だけではなく，床にデザインを表示するツールとしての用途を与える．さらに，マットを配置したいスペースに必要なマット数を直感的に把握することで，育児の負担軽減が期待できる．
EarHover：ヒアラブルデバイスにおける音漏れ信号を用いた空中ジェスチャ認識
本研究では，ヒアラブルデバイスへの空中ジェスチャ入力を可能にする新しいジェスチャ認識手法“EarHover” を提案します．本手法は，ヒアラブルデバイス特有の音漏れ現象に着目します．本研究では，有効な27 種類のジェスチャの中から，信号の識別性とユーザの受容性の観点から，7 種類のジェスチャを選択しました．その後，これらの7 種類のジェスチャとニュートラル状態の計8 状態のデータをインイヤー型/オーバーイヤー型の2 つのプロトタイプデバイスを用いて収集し，深層学習による認識性能の評価を行いました．実験の結果，インイヤー型/オーバーイヤー型デバイスのそれぞれのF-score は78.7%/73.4%でした．さらに，5 種類のジェスチャに絞ることで，F-score は6 状態で86.2%/82.5% でした．
SkinRing: 装着方向に依らない指側面でのジェスチャ入力可能なリング型デバイス
本研究では，装着方向にかかわらず指側面でのジェスチャ入力を可能にするリング型デバイスSkinRing を提案する．SkinRing は，8個の反射型光センサがリングに取り付けられたもので，人差し指に装着し，親指が人差し指に触れた際の皮膚変形情報を取得することでジェスチャ識別を行う．さらに，初めに手の開閉動作によるキャリブレーションを行うことにより，装着時のリングの回転方向に依存しない入力が可能である．9種類のジェスチャの識別精度を検証した結果，87.8％の平均識別精度を示した．
バイオリンの運弓動作計測による初心者と経験者の差異分析
バイオリンは有名で人気の高い楽器の1 つだが，習得は難しく時間がかかる．特に右手の運弓動作は音色を決定づける重要な要素であるが，複雑で練習や再現，指導が困難である．そこで，練習支援や記録を目的として，バイオリンの運弓動作の測定や分析が多く研究されてきた．本研究では運弓動作のうち弓圧に着目する．初心者と経験者の運弓動作を計測し，比較することにより，初心者への適切なフィードバック方法を検討する．
Converting Tatamis into Touch Sensors by Measuring Capacitance
This document summarizes a research paper that proposes a method to convert tatami floor mats into touch sensors by measuring capacitance. Conductive sheets are placed under the tatami surface. When a person contacts the tatami, capacitance is measured between the sheets and their skin to detect the touch position. The system identifies 12 hand gestures with approximately 90% accuracy. Future work includes enabling multi-touch detection and using the sensors for footprint tracking and pose estimation.
Pinch Force Measurement Using a Geomagnetic Sensor
This document proposes measuring pinch force using the geomagnetic sensor in a smartphone. A device with embedded magnets and springs is attached to the smartphone. As force is applied, the magnet's distance from the sensor changes, altering the magnetic flux density. Measurements found a strong correlation between force and magnetic flux density. Future work includes testing different smartphone models and collecting user feedback to improve usability.
Smartphone-Based Teaching System for Neonate Soothing Motions
This document describes a proposed smartphone-based teaching system to help first-time caregivers learn how to properly soothe neonates. The system uses sensors in a stuffed toy and a smartphone to capture posture angles and acceleration during cradling motions. It provides real-time feedback on the user's form compared to expert cradling motions. An experiment tested the system's effectiveness in improving users' cradling posture after training compared to just watching a video. Results showed the system helped users better match the expert's inclination angle, indicating it could help ensure neonate safety by teaching proper neck support. Future work is needed to improve measurement accuracy and further validate the system.
Tactile Presentation of Orchestral Conductor's Motion Trajectory
This document proposes presenting a conductor's motion trajectory tactilely for visually impaired musicians using vibrators. It describes capturing conducting movements, mapping them to vibrators, and using tactile apparent movement. An experiment found trajectory presentation helped predict beat timing better than single vibrations, especially for tempo changes and start cues. Future work includes developing a universal device.
TouchLog: Finger Micro Gesture Recognition Using Photo-Reflective Sensors
The researchers developed a fingernail-sized device using 7 photo-reflective sensors to detect finger microgestures based on fingertip skin deformation. They implemented a random forest classifier to recognize 11 gestures with an average accuracy of 91.1% for the general model and 91.5% for the individual model. Future work will focus on addressing limitations like user dependence and developing a device that can be worn comfortably for real-world use.
Seeing the Wind: An Interactive Mist Interface for Airflow Input
Human activities can introduce variations in various environmental cues, such as light and sound, which can serve as inputs for interfaces. However, one often overlooked aspect is the airflow variation caused by these activities, which presents challenges in detection and utilization due to its intangible nature. In this paper, we have unveiled an approach using mist to capture invisible airflow variations, rendering them detectable by Time-of-Flight (ToF) sensors. We investigate the capability of this sensing technique under different types of mist or smoke, as well as the impact of airflow speed. To illustrate the feasibility of this concept, we created a prototype using a humidifier and demonstrated its capability to recognize motions. On this basis, we introduce potential applications, discuss inherent limitations, and provide design lessons grounded in mist-based airflow sensing.
Identification and Authentication Using Clavicles
Identification and Authentication Using Clavicles
Yohei Kawasaki, Yuta Sugiura
2023 62nd Annual Conference of the Society of Instrument and Control Engineers (SICE), Mie, Japan, 2023
Estimation of Violin Bow Pressure Using Photo-Reflective Sensors
Estimation of Violin Bow Pressure Using Photo-Reflective Sensors presents a method for quantitatively estimating bow pressure during violin playing using photo-reflective sensors attached to the bow. Five sensors measure the distance between the bow stick and hair, which changes with applied pressure. A random forest regression model is trained on sensor distance values and actual pressure measurements to estimate pressure based solely on sensor values. In experiments, the model estimated bow pressure with an R2 of 0.84, MAE of 0.11N, and MAPE of 19.1% when tested on data from an experienced violinist. The goal is to provide visual feedback to support practice by quantifying bow pressure.
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ヒアラブルへの入力を想定したユーザ定義型ジェスチャ調査と IMUセンサによる耳タッチジェスチャの認識
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EarAuthCam: Personal Identification and Authentication Method Using Ear Image...
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Converting Tatamis into Touch Sensors by Measuring Capacitance
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TouchLog: Finger Micro Gesture Recognition Using Photo-Reflective Sensors
TouchLog: Finger Micro Gesture Recognition Using Photo-Reflective Sensors
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Digital Health in India_Health Informatics Trained Manpower _DrDevTaneja_15.0...
Digital India will need a big trained army of Health Informatics educated & trained manpower in India.
Presently, generalist IT manpower does most of the work in the healthcare industry in India. Academic Health Informatics education is not readily available at school & health university level or IT education institutions in India.
We look into the evolution of health informatics and its applications in the healthcare industry.
HIMMS TIGER resources are available to assist Health Informatics education.
Indian Health universities, IT Education institutions, and the healthcare industry must proactively collaborate to start health informatics courses on a big scale. An advocacy push from various stakeholders is also needed for this goal.
Health informatics has huge employment potential and provides a big business opportunity for the healthcare industry. A big pool of trained health informatics manpower can lead to product & service innovations on a global scale in India.
一比一原版(USF毕业证)旧金山大学毕业证如何办理
USF毕业证offer【微信95270640】《旧金山大学毕业证购买》《如何办理USF毕业证旧金山大学文凭学历》Q微信95270640实体公司，专业可靠，办理毕业证办美国成绩单,做加拿大文凭学历认证,办新西兰学位证，学位证书是什么?《制作旧金山大学毕业证多少钱》《USF学历证书丢了怎么办理》办澳洲文凭认证，办留信网认证（网上可查，实体公司，专业可靠）
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6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。头贼脑的倒也逗人喜爱日上三竿时山娃总爱窜进自家瓜棚里跟小伙伴们坐着聊天聊着聊着便忍不住往瓜田里逡巡一番抱起一只硕大的西瓜用石刀劈开抑或用拳头砸开每人抱起一大块就啃啃得满嘴满脸猴屁股般的红艳大家一个劲地指着对方吃吃地笑瓜裂得古怪奇形怪状却丝毫不影响瓜味甜丝丝的满嘴生津遍地都是瓜横七竖八的活像掷满了一地的大石块摘走二三只爷爷是断然发现不了的即便发现爷爷也不恼反而教山娃辨认孰熟孰嫩孰甜孰淡名义上是护瓜吃
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The Importance of Black Women Understanding the Chemicals in Their Personal C...
Certain chemicals, such as phthalates and parabens, can disrupt the body's hormones and have significant effects on health. According to data, hormone-related health issues such as uterine fibroids, infertility, early puberty and more aggressive forms of breast and endometrial cancers disproportionately affect Black women. Our guest speaker, Jasmine A. McDonald, PhD, an Assistant Professor in the Department of Epidemiology at Columbia University in New York City, discusses the scientific reasons why Black women should pay attention to specific chemicals in their personal care products, like hair care, and ways to minimize their exposure.
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Hypotension and role of physiotherapy in it
This particular slides consist of- what is hypotension,what are it's causes and it's effect on body, risk factors, symptoms,complications, diagnosis and role of physiotherapy in it.
This slide is very helpful for physiotherapy students and also for other medical and healthcare students.
Here is the summary of hypotension:
Hypotension, or low blood pressure, is when the pressure of blood circulating in the body is lower than normal or expected. It's only a problem if it negatively impacts the body and causes symptoms. Normal blood pressure is usually between 90/60 mmHg and 120/80 mmHg, but pressures below 90/60 are generally considered hypotensive.
Pneumothorax and role of Physiotherapy in it.
This particular slides consist of- what is Pneumothorax,what are it's causes and it's effect on body, risk factors, symptoms,complications, diagnosis and role of physiotherapy in it.
This slide is very helpful for physiotherapy students and also for other medical and healthcare students.
Here is a summary of Pneumothorax:
Pneumothorax, also known as a collapsed lung, is a condition that occurs when air leaks into the space between the lung and chest wall. This air buildup puts pressure on the lung, preventing it from expanding fully when you breathe. A pneumothorax can cause a complete or partial collapse of the lung.
FACIAL NERVE
The facial nerve, also known as cranial nerve VII, is one of the 12 cranial nerves originating from the brain. It's a mixed nerve, meaning it contains both sensory and motor fibres, and it plays a crucial role in controlling various facial muscles, as well as conveying sensory information from the taste buds on the anterior two-thirds of the tongue.
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VEDANTA AIR AMBULANCE SERVICES IN REWA AT A COST-EFFECTIVE PRICE.pdf
Exercise Measurement using a Built-in Camera in a Mobile Device(AsianCHI2020)
- 1. 02 Recognition Principle ・ 30 feature points are extracted by using the Single Face Tracker for Unity Plugin [3]. ・The system uses 62 parameters: 30 feature points × 2 (x and y) + two distances. ・Obtained data is divided into every frames. ・After removing a trend, it applies Fast Fourier Transform (FFT) and uses half of all dimensions’ frequency components for making a Support Vector Machine’s (SVM’s) classifier. Exercise Measurement using a Built-in Camera in a Mobile Device Kaho Kato Keio University Chengshuo Xia Keio University Yuta Sugiura Keio University 01 Introduction Background Problem ・Exercise is important to keep our health. ・Our motivation for exercise can be improved by using the systems that can measure and record our exercises automatically. ・Many studies have been proposed that can measure exercises automatically by cameras. ・In most measurement methods, users need a large space to capture a whole body within an angle of view of a camera. ・Inaba[1] proposed an exercise measurement method using the human face’s feature points got via mobile devices. ・We investigated what kind of movements can be identified by the face’s feature points. Approach [3]ULSeeInc.2017.SingleFaceTrackerPlugin(LiteVersion-30FaceTrackingPoints)-AssetStore.(2017).(Accessedon01/13/2020). Contact: kaho_0128@keio.jp 03 Recording Application ・An application based on Unity is developed to record and uses a built-in camera video on a mobile device. ・During excising, it tracks 30 feature points on the face. ・When a user completes, it writes data into CSV files. 04 Kind of Exercise ・9 kinds of exercise were defined, referring to the research of Hashizume[2]. ・Standing exercises: To train the lower half of the body. A user can do anywhere. ・On the floor exercises: To train the trunk of the body. They need a specific place. ・Limitations The system- needs a high frame rate to get smooth data. - is vulnerable to darkness or shielding. - needs a user to keep the face putting within an angle of a camera view. ・Future Works We will - investigate how many feature points are suitable for classification to reduce calculate costs. - gather more data to derive a more accurate model. 05 Evaluation 06 Limitations & Future Works ・Participants: 10 people. ・Order of exercises: Randomly. ・Learning data: Leave One Participant Out cross-validation ・The average accuracy: About 89.4%. [1]KonomiInabaetal.2019.Tablet ApplicationforHeel-raiseTraining byDetectingFaceMovement.In EntertainmentComputing2019,Vol. 2019.393–397. ・Walking ・Jogging ・High knee raise exercise ・Heel raise and lower exercise ・Squat exercise ・No exercise(Standing straight) ・Sit-ups exercise ・Push-ups exercise ・Back extension exercise Standing On the floor [2]HiroshiHashizumeetal.2014. Developmentand evaluationofavideo exerciseprogramforlocomotive syndromeintheelderly.Modern Rheumatology24,2(2014),250–257.