To tackle this challenge, we explore design options for an interactive artifact that can effectively support yoga practice at home, potentially replacing professional personal trainers. Through this series of context-driven exploratory studies, we demonstrate approaches to exploring design options for technology-assisted home yoga.
Background
The main findings from another user study show that the preference for the type of feedback is highly dependent on the level of expertise in yoga. Furthermore, the results of the phase detector development study show that the per-user classifiers perform reasonably well in all positions, taking into account many current judgments to identify each breathing phase.
Thesis Statement
From preliminary user studies with yoga practitioners, we discovered three aspects of a yoga practice that our population is concerned about: breathing, posture, and motivation. Moreover, user-specific classifiers for identifying three yoga poses show promising results, expanding the applicable areas of the respiratory phase detector.
Thesis Structure
This is divided into two different sections: one on breathing exercises for meditative purposes and the other on using breathing patterns as input to a system. This section introduces contact and non-contact based sensing methods and addresses the challenge posed in our study context.
Yoga in HCI Studies
Then the requirements for designing a successful feedback strategy are described, followed by feedback strategies used to reinforce breathing exercises. These works also point out that no single aspect of yoga is remarkably essential to pursuing a practice.
Breathing in HCI Studies
Breathing for Self-Relaxation
Breathing as a Control Mechanism
Another aspect of breathing that has attracted many HCI researchers is the characterization of breathing patterns for the natural user interface. Some iconic examples where variations in breathing patterns are used as a control mechanism are breath-controlled games such as FlappyBreath [20] and ChillFish [21].
Respiration Sensing
Contact-based Methods
Another exemplary work is Broncomatic [22], in which the patterns and speed of the user's breathing are mapped to the direction and speed of rotation of a stationary bronco ride. Previous studies show that breathing can be voluntarily controlled and breath can mark the duration and stability of the breathing pattern.
Noncontact-based Methods
Feedback Strategies
Terminology: Guidance, Feedback, and Intervention
For example, when a user performs poorly while using a system, whether due to the user's ignorance of proper system use or the difficulty of a task, providing specific instructions to help a user perform better to do more effectively than raising an error message. . Here, the instructions given to the user are guidance, but they are also feedback as they are provided as a result of an action the user has taken.
Design of a Successful Feedback Strategy
In other words, the definition does not specify the point at which the interruption occurs during a sequence of events. From this perspective, the terms intervention, feedback and guidance used in this thesis have the same meaning: any type of intervention provided in response to an action taken by the system user.
Interventions to Enhance Breathing
This type of method is often used in responsive environments in the form of an interaction mechanism, where users' breathing patterns activate and manipulate the surrounding architecture. It is believed that this type of interaction also allows users to gain greater control of their breathing [1].
Overview
User Study Part I: Investigating the Usage Context
Aim
Materials and Methods
In order to clarify the instructor's point of view, semi-structured interviews were conducted with two certified yoga instructors. Questions focus on the instructor's work experience, class structure and curriculum, major concerns among beginning students, strategies for motivating students, and knowledge of adjusting the level of difficulty in a group exercise.
Results and Discussion
So I actually want to know the most important points and warnings for a pose. In addition, individual differences in flexibility and balance have a major influence on body alignment and posture. For example, P7 reported, “I have less flexibility in the back muscles of my thighs, so I have difficulty with poses that require these muscles, even when the poses are at a basic level.” When a practitioner is having difficulty during a yoga class, the instructor “slows down the pace and shows variations in the pose,” as P9 and P10 mentioned. P8 stated, “I started yoga by watching a popular video tutorial, but the video is inefficient because it can't tell you how you're doing” and explained, “There's an ah-ha moment where I do something wrong and the instructor comes by to correct my posture.” However, this is not possible if you practice alone at home.
P2 described: “I thought I could do it [holding the tree pose], but I couldn't hold the pose for long because I was swaying”. P4 noted, "When I only practice with video clips, I skip parts that seem difficult." Holding time for a pose seems to be an obvious problem, especially in a group class as many interviewees explained how they tend to ignore the instructor's verbal cues to keep their pace.
User Study Part II: Navigating the Design Concepts
Aim
The codes grouped under motivation are about evaluating the poses for the best physical benefits in the body after the practice. P6 described: “I feel like I'm doing something wrong when I don't feel the tension from a pose. I often ask the instructor if I should feel the tension in this part of the body or not." Several others noted that they like to focus attention on tense parts of their body when practicing yoga as the tension brings personal satisfaction.
P6 said, “When the instructor explains the benefits of the pose, I tend to focus my attention on the specific body part.
Materials and Methods
The reason for this is that all the practitioners were aware of the fact that yoga is not an intense fitness exercise that produces obvious physical changes in the body in the short term. If they had any questions, they were allowed to interrupt the interviewer in the middle of the story. At the end of each concept, they were asked a set of prepared questions about each of the concepts.
When all concepts are shown, participants were given a summary map with nine storyboards as shown in Figure 2.
Results and Discussion
P4 illustrated his reaction to the idea: “I think it would be fun, but I'll definitely become more calculating. Not all of the yoga practitioners who participated in this interview liked the idea of wearing a VR device while practicing yoga. Others liked the idea because it's feedback that we can perceive when we close our eyes.
Some people strongly opposed the idea that he identified himself as an advanced yoga practitioner, saying, "holding a posture for a long time is not bad for you." Other practitioners have mentioned that constant vibration on the wrist would be distracting because it is the feedback you cannot ignore while performing a pose.
Design of Biofeedback-based Yoga Mat for Breathing Training
Design Implications
Proposed Design of Biofeedback-based Yoga Mat
The details of the development of this breathing phase detector are described in the next chapter. In addition, we develop a cost-effective respiratory phase detector for home exercises using IMUs based on previous work. For this reason, the detection mechanism must be robust to both body postures and ambient noise.
Here the development of a respiratory phase detector for detecting the four respiratory phases is presented in detail.
Respiration Phase Detector Prototype
One IMU sensor is placed on top of a person's solar plexus as suggested in [46], and the other is placed on the back of the person in a position parallel to that of the solar plexus. The relative rotation and acceleration differences between two sensors from the gyroscope and accelerometer are used to identify the respiration phases. The rotational changes in the y-axis reflect expansion and compression of the diaphragm, and acceleration in the x-axis represents the orientation of the sensor.
Relative acceleration and rotation are derived from two sets of raw values of rotation and acceleration. a) Respiration phase detector prototype, (b) VR IMU orientation and three axes.
Data Collection Study
- Aim
- Participants
- Experimental Setup
- Materials and Methods
The sensors are configured to receive rotation on the y-axis, acceleration on the x-axis, and transmit this raw data wirelessly to Processing via Zigbee. No limitations were placed on the potential end users of the developed artifact. The suggested breathing training system is primarily designed for beginner yoga practitioners who may not have been exposed to any type of breathing practice in the past.
When sensor calibration is complete, participants watch video tutorials for diaphragmatic breathing and each of the postures.
Building Classifiers
- Data Preprocessing
- Feature Vectors
- Comparison with Ground Truth
- Classifiers and Feature Selection
- Classifier Performance
- Respiration Phase Detection
- Pose Detection
However, the average performance results of the classifiers per user summarized in Table 3 show that the generalized classifier cannot be modeled. The average performance results of the classifiers per user for detecting three poses are summarized in Table 5. The average classification accuracy of the classifiers per user shows that our prototype is able to correctly detect three poses for each user.
Our assumption is based on the fact that the scores reported by most classifiers for each user for the easy pose are relatively high.
Limitations and Future Work
The application can provide a summary report of practiced pose types, allowing practitioners to maintain a balance between poses in their routine. There are a number of requirements that must be met in order to conduct this research. Before this, we need to ensure that building and storing machine learning models on the mobile application is feasible.
If it is feasible to train and use the classifier, we need to test and finalize the number of breaths required to build the classifier with reasonable performance.
Conclusion
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Cauchard, “Breeze: Sharing biofeedback through wearable technologies,” in Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, ser. Feijs, “Biofidget: Biofeedback for respiratory training using an augmented fidget spinner,” in Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, ser. Peripheral paced respiration: influencing user physiology during information work,” in Proceedings of the 24th annual ACM symposium on User interface software and technology.
