Diagnosis of Scoliosis in Juvenile Patients

In this paper, a wearable device used to monitor the posture variations. This device is useful in early detection and monitoring of patient having spine related disease such as scoliosis, kyphosis. Scoliosis is a 3-dimensional deformation of spine. The most common characteristics are bending of backbone in coronal plane and rotation of vertebrae, which results in various deformations of human postures. It mostly occurs in juvenile stage (3-10 years). The existing system consists of wearable sensor network for posture data acquisition, wireless data transmission and conventional smartphone for data processing. The biofeedback device helps to improve the self-awareness in natural environment, but it is not suitable in case of severe deformity. The flex sensor used because of its High level of reliability, consistency, repeatability and harsh temperature resistance. Keywords: scoliosis, microcontroller, flex sensor

A Wearable Biofeedback Device to Increase Gait Swing Time Could Have Positive Effects on Gait among Older Adults

Older adults walk with a shorter stride length, reduced hip range of motion (ROM) and higher cadence. These are signs of reductions in walking ability. This study investigated whether using a wireless smart insole system that monitored and provided biofeedback to encourage an extension of swing time could increase stride length and hip flexion, while reducing the cadence. Seven older adults were tested in this study, with and without the biofeedback device, in an outdoor environment. Gait analysis was performed by using GaitRite system and Xsens MVN. Repeated measures analysis demonstrated that with biofeedback, the swing time increased by 6.45%, stride length by 4.52% and hip flexion by 14.73%, with statistical significance. It also decreased the cadence significantly by 5.5%. This study has demonstrated that this smart insole system modified positively the studied gait parameters in older adults and has the potential to improve their walking ability.

Towards a Resilience to Stress Index Based on Physiological Response: A Machine Learning Approach

This study proposes a new index to measure the resilience of an individual to stress, based on the changes of specific physiological variables. These variables include electromyography, which is the muscle response, blood volume pulse, breathing rate, peripheral temperature, and skin conductance. We measured the data with a biofeedback device from 71 individuals subjected to a 10-min psychophysiological stress test. The data exploration revealed that features’ variability among test phases could be observed in a two-dimensional space with Principal Components Analysis (PCA). In this work, we demonstrate that the values of each feature within a phase are well organized in clusters. The new index we propose, Resilience to Stress Index (RSI), is based on this observation. To compute the index, we used non-supervised machine learning methods to calculate the inter-cluster distances, specifically using the following four methods: Euclidean Distance of PCA, Mahalanobis Distance, Cluster Validity Index Distance, and Euclidean Distance of Kernel PCA. While there was no statistically significant difference (p>0.01) among the methods, we recommend using Mahalanobis, since this method provides higher monotonic association with the Resilience in Mexicans (RESI-M) scale. Results are encouraging since we demonstrated that the computation of a reliable RSI is possible. To validate the new index, we undertook two tasks: a comparison of the RSI against the RESI-M, and a Spearman correlation between phases one and five to determine if the behavior is resilient or not. The computation of the RSI of an individual has a broader scope in mind, and it is to understand and to support mental health. The benefits of having a metric that measures resilience to stress are multiple; for instance, to the extent that individuals can track their resilience to stress, they can improve their everyday life.

Design and Development of GSR Biofeedback Device

It has been a long time that human is interested in learning how to control involuntary actions such as heartbeat, blood pressure, breathing, etc., so a lot of research has been done on this issue so far. One of the methods using in this field is biofeedback, in which someone can roughly control an involuntary action or having better control over some voluntary actions such as muscle contraction through some visual or audio feedback from those actions. This study is to design and development of one biofeedback instrument, which is GSR (Galvanic Skin Response), and examine some signals that have been taken by this device.

Development and usability of biofeedback system for water resistance therapy using sensor

Purpose: The purpose of this study was to develop a water cup device for voice therapy as a biofeedback device for water resistance therapy (WRT), one of the semi-occluded vocal tract exercises (SOVTEs) using sensors. In addition, we explore the usefulness of the system for training in voice therapy by implementing water resistance phonation through newly developed devices.Methods: Using Arduino, the water resistance value was measured using a water level sensor, and a system was developed to visually implement the water resistance value and duration of exhalation and vocalization according to the change in water level caused by bubbles. Visual feedback was provided using LED sensors that represent colors according to the height of the water level. The WRT step was performed on six normal adults (male 3 and female 3) to implement changes in water level change amplification rate according to tube diameter and depth, and quantitatively analyzed.Results: The experiment showed that different LED colors were displayed depending on the resistance value of the water level. The LED’s brightness decreased as the width of the silicone tube diameter became larger in the bubble according to the tube diameter. Moreover, compared to 5 mm or 7 mm, a tube diameter of 10 mm showed the lowest amplification rate, regardless of with or without phonation. A depth of 2 cm, with the tube tip submerged in water, demonstrated the lowest amplification rate with or without phonation, compared to 4, 7, and 10 cm.Conclusions: The newly developed cup device for water resistance therapy was easy to give visual feedback according to changes in water level and helped to identify objectively by quantifying the performance of the target. This system may help clinicians and patients not only in clinical situations but also in practice at home during voice training.

Repurposing an EMG Biofeedback Device for Gait Rehabilitation: Development, Validity and Reliability

Gait impairment often limits physical activity and negatively impacts quality of life. EMG-Biofeedback (EMG-BFB), one of the more effective interventions for improving gait impairment, has been limited to laboratory use due to system costs and technical requirements, and has therefore not been tested on a larger scale. In our research, we aimed to develop and validate a cost-effective, commercially available EMG-BFB device for home- and community-based use. We began by repurposing mTrigger® (TJM Electronics, Warminster, PA, USA), a cost-effective, portable EMG-BFB device, for gait application. This included developing features in the cellphone app such as step feedback, success rate, muscle activity calibration, and cloud integration. Next, we tested the validity and reliability of the mTrigger device in healthy adults by comparing it to a laboratory-grade EMG system. While wearing both devices, 32 adults walked overground and on a treadmill at four speeds (0.3, 0.6, 0.9, and 1.2 m/s). Statistical analysis revealed good to excellent test–retest reliability (r > 0.89) and good to excellent agreement in the detection of steps (ICC > 0.85) at all speeds between two systems for treadmill walking. Our results indicated that mTrigger compared favorably to a laboratory-grade EMG system in the ability to assess muscular activity and to provide biofeedback during walking in healthy adults.

A Mediterranean-Based Ketogenic Diet Application Compared to a Calorie-Restricted Low-Fat Diet Application on Cardiometabolic Risk in Adults With Overweight or Obesity

Objectives To determine the effects of a Mediterranean-based ketogenic weight loss diet app paired with a breath acetone biofeedback device compared to a relevant comparator arm on blood biomarkers of cardiometabolic risk in a hands-off, real-world setting. Methods Participants (N = 155) with overweight/obesity (41 ± 11 years, BMI = 32 ± 9 kg/m2, 71% female) were randomized to one of two diet groups, with interventions delivered entirely via mobile app without in-person interaction with study staff: i) a Mediterranean-based ketogenic diet paired with a breath acetone biofeedback device (Keyto); or ii) a calorie-restricted low-fat diet (WW). Participants took daily weight measurements on an at-home wireless scale and a third-party laboratory obtained fasted blood samples at baseline and at 12 weeks. Results Based on intention-to-treat analysis, participants in the Keyto group lost more weight than those in the WW group (−3.1 kg; 95% CI, −4.6 kg to −1.5 kg; P < 0.001). Likewise, those randomized to the Keyto app experienced greater improvements in markers of glycemic control (HbA1c; −0.2%; 95% CI, −0.3% to −0.1%; P < 0.001) and hepatic function (alanine aminotransferase, alkaline phosphatase, globulin; P < 0.01) compared to the WW group. In follow-up analyses accounting for baseline weight and change in body mass, the effects of group assignment on these cardiometabolic risk markers were found to remain significant independent of differences in weight loss between groups. No other differences in blood markers, including lipids and lipoproteins, were found. Conclusions Among adults with overweight or obesity, assignment to the Keyto app, as compared to the WW app, resulted in greater weight loss and cardiometabolic improvements that appeared to be independent of weight loss. These findings suggest that a Mediterranean-based ketogenic diet app paired with a breath acetone biofeedback device is effective at improving cardiometabolic health beyond weight loss in a real-world setting. Funding Sources Canadian Institutes of Health Research (CIHR), Michael Smith Foundation for Health Research (MSFHR), Mitacs Accelerate International with Keyto Inc. as the industry partner.

Sitting Posture during Prolonged Computer Typing with and without a Wearable Biofeedback Sensor

Prolonged sitting combined with an awkward posture might contribute to the increased risks of developing spinal pain. Maintaining an upright sitting posture is thus often suggested, especially nowadays when people spend longer periods in the sitting posture for occupational or leisure activities. Many types of assistive devices are commercially available to help computer users maintain an upright sitting posture. As the technology advances, wearable sensors that use microelectromechanical technology are designed to provide real-time biofeedback and promote adjusting posture actively. However, whether such wearable biofeedback sensors could assist adjusting sitting posture in computer users during prolonged typing remains unknown. This study aimed to investigate the effects of a wearable biofeedback sensor on maintaining an upright sitting posture. Twenty-one healthy young adults were recruited and performed a 1-h computer typing task twice, with and without using the active biofeedback device. The sagittal spinal posture during computer typing was measured using a three-dimensional motion analysis system. Using the wearable biofeedback sensor significantly decreased the neck flexion (p < 0.001), thoracic kyphotic (p = 0.033), and pelvic plane (p = 0.021) angles compared with not using the sensor. Computer users and sedentary workers may benefit from using wearable biofeedback sensors to actively maintain an upright sitting posture during prolonged deskwork.