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Smart gyms need smart mirrors: design of a smart gym concept through contextual inquiry
Abstract
Much research on smart environments has focused on homes and offices. With increasing physical inactivity and its health effects, augmenting gyms to motivate, assist and coach users to track and achieve their fitness goals is important. In this paper, we propose using smart mirrors to automatically detect and count repetitions of exercises, and to provide coaching, motivation and information to users. We present the concept and use cases, developed with 7 users (novices and fitness fanatics) through contextual inquiry, and discuss how the concept can be realized with current technologies.
... A central challenge for instructional videos stems from how the user, in these settings, is learning on their own from pre-recorded material, which leads to a lack of feedback and personalised instructions [51,77], and to having to rely on their own imitation capacity to learn movements, which in itself is challenging [29]. To date, research addressing this challenge has mostly focused on augmented feedback, i.e., providing trainees with information about their movements to help them assess their performance in a variety of contexts, e.g.,: strength training [3,20,59], dance [2,12], yoga [15,56,72], physiotherapy [1,38,68], and sports [60,76]. ...
Instructional videos for physical training have gained popularity in recent years among sport and ftness practitioners, due to the proliferation of afordable and ubiquitous forms of online training. Yet, learning movement this way poses challenges: lack of feedback and personalised instructions, and having to rely on personal imitation capacity to learn movements. We address some of these challenges by exploring visual cues’ potential to help people imitate movements from instructional videos. With a Research through Design approach, focused on strength training, we augmented an instructional video with diferent sets of visual cues: directional cues, body highlights, and metaphorical visualizations. We tested each set with ten practitioners over three recorded sessions, with follow-up interviews. Through thematic analysis, we derived insights on the efect of each set of cues for supporting movement learning. Finally, we generated design takeaways to inform future HCI work on visual cues for instructional training videos.
... The screens of wearables and smartphones are personalized and offer efficient communication, but they still require users to look at them, which increases users' cognitive load and shifts their focus [57]. A big screen mounted on a wall or a training machine can make the information easier to digest [30] and mitigate the burden of cognitive load involved in processing information from a smartphone or wearable. (These ambient interfaces will be discussed further in later sections.) ...
There is growing consumer demand for digital technologies that help users track, motivate, and receive coaching for both aerobic and anaerobic activities. In this article, we provide a review of existing technological advances in tracking, coaching, and motivating users during indoor training in contexts such as gymnasiums. This study lists the advantages and limitations of various apparatuses and applications used for this purpose. Our review and discussion are intended to help entrepreneurs and engineers improve their products to better meet users? needs and aid researchers in identifying potential new areas.
... Furthermore, smart mirrors have become a popular interface element in both research [50,6,26] and commercially. In recent years, we have seen smart mirrors extend beyond functional devices, being employed in bespoke, open-ended interfaces that promote ludic engagement [60,30]. ...
... Furthermore, smart mirrors have become a popular interface element in both research [50,6,26] and commercially. In recent years, we have seen smart mirrors extend beyond functional devices, being employed in bespoke, open-ended interfaces that promote ludic engagement [60,30]. ...
This paper introduces a new form of real-time affective interface that engages the user in a process of conceptualisation of their emotional state. Inspired by Barrett's Theory of Constructed Emotion, `Mirror Ritual' aims to expand upon the user's accessible emotion concepts, and to ultimately provoke emotional reflection and regulation. The interface uses classified emotions -- obtained through facial expression recognition -- as a basis for dynamically generating poetry. The perceived emotion is used to seed a poetry generation system based on OpenAI's GPT-2 model, fine-tuned on a specially curated corpus. We evaluate the device's ability to foster a personalised, meaningful experience for individual users over a sustained period. A qualitative analysis revealed that participants were able to affectively engage with the mirror, with each participant developing a unique interpretation of its poetry in the context of their own emotional landscape.
... Smart mirrors for personal training can replace the regular mirrors in most gyms. 43 In this context, members could receive guidance, motivation, and encouragement for particular exercises. The same scenario applies to physical therapy, whereby the patient uses biofeedback in performing the recommended exercises. ...
Abstract Inexpensive embedded computing and the related Internet of Things technologies enable the recent development of smart products that can respond to human needs and improve everyday tasks in an attempt to make traditional environments more “intelligent”. Several projects have augmented mirrors for a range of smarter applications in automobiles and homes. The opportunity to apply smart mirror technology to healthcare to predict and to monitor aspects of health and disease is a natural but mostly underdeveloped idea. We envision that smart mirrors comprising a combination of intelligent hardware and software could identify subtle, yet clinically relevant changes in physique and appearance. Similarly, a smart mirror could record and evaluate body position and motion to identify posture and movement issues, as well as offer feedback for corrective actions. Successful development and implementation of smart mirrors for healthcare applications will require overcoming new challenges in engineering, machine learning, computer vision, and biomedical research. This paper examines the potential uses of smart mirrors in healthcare and explores how this technology might benefit users in various medical environments. We also provide a brief description of the state-of-the-art, including a functional prototype concept developed by our group, and highlight the directions to make this device more mainstream in health-related applications.
Health is a precious gift from God. Both physical and mental health is equally important for living a quality life. Negligence towards mental health creates a lot of serious health problems affecting both physical health and society. Mental health is associated with better performance, high efficiency, and lesser work environment mishaps. Internet of Things technologies can possibly create smart products that can react to human needs and improve the quality of life and can make traditional environments more favorable and intelligent. One such internet of things solution is the design and development of smart mirrors. The opportunity to apply smart technology to healthcare to foresee and to monitor aspects of mental health is a natural but mostly underdeveloped idea. Although several smart mirror solutions have been proposed for different purposes, it has not been developed for the treatment of depression. We believe that smart mirrors involving a combination of hardware and software could identify depression as well as offer feedback for corrective measures and remedial activities. This paper examines the potential use of a smart mirror in healthcare and examines how this technology might benefit users in resolving depression. We present the design and development of a smart mirror that can diagnose and provide digitized treatment to resolve depression. The developed mirror is tested on humans, and from the obtained results, it is concluded that the developed mirror is more accurate and inexpensive as compared to existing smart mirrors.
Health is a precious gift from God. Both physical and mental health is equally important for living a quality life. Negligence towards mental health creates a lot of serious health problems affecting both physical health and society. Mental health is associated with better performance, high efficiency, and lesser work environment mishaps. Internet of Things technologies can possibly create smart products that can react to human needs and improve the quality of life and can make traditional environments more favorable and intelligent. One such internet of things solution is the design and development of smart mirrors. The opportunity to apply smart technology to healthcare to foresee and to monitor aspects of mental health is a natural but mostly underdeveloped idea. Although several smart mirror solutions have been proposed for different purposes, it has not been developed for the treatment of depression. We believe that smart mirrors involving a combination of hardware and software could identify depression as well as offer feedback for corrective measures and remedial activities. This paper examines the potential use of a smart mirror in healthcare and examines how this technology might benefit users in resolving depression. We present the design and development of a smart mirror that can diagnose and provide digitized treatment to resolve depression. The developed mirror is tested on humans, and from the obtained results, it is concluded that the developed mirror is more accurate and inexpensive as compared to existing smart mirrors.
Introduction
This study evaluates whether a health club membership is associated with meeting the US physical activity (PA) guidelines and/or favorable cardiovascular health.
Methods
Using cross-sectional data of health club members (n = 204) and non-members (n = 201) from April to August 2013, this is the first study to our knowledge to examine a health club membership in relation to objectively measured cardiovascular health indicators including resting blood pressure, resting heart rate, body mass index, waist circumference, and cardiorespiratory fitness based on a non-exercise test algorithm. To determine the total PA and sedentary time, this study used a comprehensive PA questionnaire about both aerobic and resistance activities at the health club, as well as lifestyle activities in other settings, which was developed based on the International Physical Activity Questionnaire (IPAQ).
Results
The odds ratios (95% confidence interval) of meeting either the aerobic, resistance, or both aerobic and resistance PA guidelines for members compared to non-members were 16.5 (9.8–27.6), 10.1 (6.2–16.3), and 13.8 (8.5–22.4), respectively. Significant associations of health club membership with more favorable cardiovascular health outcomes and sedentary behavior were observed for resting heart rate (B: -4.8 b/min, p<0.001), cardiorespiratory fitness (B: 2.1 ml/kg/min, p<0.001), and sedentary time (B: -1.4 hours, p<0.001). Participants with a health club membership of >1 year had more favorable health outcomes, with a smaller waist circumference (men, B: -4.0 cm, p = 0.04; women, B: -3.4 cm, p = 0.06), compared to non-members.
Conclusions
Health club membership is associated with significantly increased aerobic and resistance physical activity levels and more favorable cardiovascular health outcomes compared to non-members. However, longitudinal, randomized controlled trials would be clearly warranted as cross-sectional data prohibits causal inferences.
Digital video content via broadcast television, Internet and other content distribution networks provide limited interaction for fitness and wellness activities. The content delivery is one-way only and provides no personalization to the pace, programming and progress of the user’s exercise routine. Furthermore, the content is to be viewed only on a screen which makes it awkward and incompatible with full-body activities such as yoga, pilates and T’ai chi. We present CloudMat, a system for context-aware personalization of fitness content with cloudenabled connected surfaces. CloudMat provides real-time closedloop feedback between the state of the user on the physical mat and the state of the content in the cloud service. Content is tagged with actuation signals where events are delegated from the screen to display on an electroluminescent lighting layer on the mat, which provides spatial guidance to the end-user. Through the sensor-layer embedded in the mat, the physical interface captures the pose and timing of the user activity and relays it to the Context-aware Personalization cloud service. This service coordinates sensing and actuation between the content stream and mat by generating pose templates and metadata files about the exercise routine to be delivered to the user. Through this interactive process between the physical mat and the content service, the feedback provided by the user performing the routine continuously adapts the pace and programming to maintain the desired user experience. We demonstrate the utility of the system and evaluate the system performance with a case study on interactive yoga.
We present a wearable textile sensor system for monitoring muscle activity, leveraging surface pressure changes between the skin and compression garment. Our first prototype is based on an element fabric resistive pressure mapping matrix with spacial resolution and refresh rate. We evaluate the prototype by monitoring leg muscles during realistic leg workouts in a gym out of the lab. The sensor covers the lower part of quadriceps of the user. The shape and movement of the two major muscles (vastus lateralis and medialis) are visible from the data visualizing during various exercises. With features extracted from spacial and temporal domains out of the pressure force mapping information, with 4 different leg exercises plus non-workout activities (relaxing, adjusting machines and walking), we have reached average recognition accuracy on a fine-grain sliding window basis, on an event basis, and spotting F1-score. We further investigate the relationships between people’s perception of the exercise quality/difficulty and the variation and consistency of the force pattern. A second prototype is also developed with tether-free to explore various placements including upper-arm, chest and lower back; a brief comparison with arm-worn EMG shows our approach is comparable on the signal quality level.
There is a large class of routine physical exercises that are performed on the ground, often on dedicated "mats" (e.g. pushups, crunches, bridge). Such exercises involve coordinated motions of different body parts and are difficult to recognize with a single body worn motion sensors (like a step counter). Instead a network of sensors on different body parts would be needed, which is not always practicable. As an alternative we describe a cheap, simple textile pressure sensor matrix, that can be unobtrusively integrated into exercise mats to recognize and count such exercises. We evaluate the system on a set of 10 standard exercises. In an experiment with 7 subjects, each repeating each exercise 20 times, we achieve a user independent recognition rate of 82.5% and a user independent counting accuracy of 89.9%. The paper describes the sensor system, the recognition methods and the experimental results. Copyright
Background:
An aging population and people's higher survival to diseases and traumas that leave physical consequences are challenging aspects in the context of an efficient health management. This is why telerehabilitation systems are being developed, to allow monitoring and support of physiotherapy sessions at home, which could reduce healthcare costs while also improving the quality of life of the users.
Objectives:
Our goal is the development of a Kinect-based algorithm that provides a very accurate real-time monitoring of physical rehabilitation exercises and that also provides a friendly interface oriented both to users and physiotherapists.
Methods:
The two main constituents of our algorithm are the posture classification method and the exercises recognition method. The exercises consist of series of movements. Each movement is composed of an initial posture, a final posture and the angular trajectories of the limbs involved in the movement. The algorithm was designed and tested with datasets of real movements performed by volunteers. We also explain in the paper how we obtained the optimal values for the trade-off values for posture and trajectory recognition.
Results:
Two relevant aspects of the algorithm were evaluated in our tests, classification accuracy and real-time data processing. We achieved 91.9% accuracy in posture classification and 93.75% accuracy in trajectory recognition. We also checked whether the algorithm was able to process the data in real-time. We found that our algorithm could process more than 20,000 postures per second and all the required trajectory data-series in real-time, which in practice guarantees no perceptible delays. Later on, we carried out two clinical trials with real patients that suffered shoulder disorders. We obtained an exercise monitoring accuracy of 95.16%.
Conclusions:
We present an exercise recognition algorithm that handles the data provided by Kinect efficiently. The algorithm has been validated in a real scenario where we have verified its suitability. Moreover, we have received a positive feedback from both users and the physiotherapists who took part in the tests.
In this paper, we present the system that aids people in wearing makeup easily and make the process enjoyable. The proposed system is the "Smart Makeup Mirror" device, which is an electronic dressing table that facilitates the process of makeup application. In this system, we place a high-resolution camera on top of a computer display. We developed some functions such as "Automatic zoom to a specific part of the face", "Display our face from various angles", and "Simulation of the lighting conditions". People who use this device for applying makeup will obtain highly satisfactory results, while also enjoying the process.
This paper will discuss the concept of a smart mirror for healthier living, the FitMirror. Many people have serious problems to get up after sleeping, to get motivated for the day, or are tired and in a bad mood in the morning. The goal of FitMirror is to positively affect the user’s feelings by increasing his/her motivation, mood and feeling of fitness. While concepts for these isolated problems exist, none of these combine them into one system. FitMirror is implemented to combine them and evaluate them in a study. It consists of a monitor with spy-foil, a Microsoft Kinect v2 and a Wii Balance Board and can recognize users and their gestures with these elements. Several hypotheses about the system regarding motivation, fun, difficulty and getting awake were investigated. Participants were grouped by the factors sportspersons and morning persons to investigate the effect based on these aspects. Results show that FitMirror can help users get awake in the morning, raise their motivation to do sports and motivate them for the day.
Orkan Telhan, and Rahul Mangharam Cloud Mat: Context-Aware Personalization of Fitness Content
- Jin Kuk
- Jungmin Jang
- Ryoo