The Efficacy of a Multicomponent Functional Fitness Program Based on Exergaming on Cognitive Functioning of Healthy Older Adults: A Randomized Controlled Trial.

BACKGROUND AND OBJECTIVES: Regular physical exercise can attenuate age-related cognitive decline. This study aimed to investigate the effect of a physical exercise multicomponent training based on exergames on cognitive functioning (CF) in older adults. RESEARCH DESIGN AND METHODS: This randomized controlled trial included older adults aged 61-78. Participants were randomly allocated to an intervention group (IG; n = 15) or active control group (CG; n = 16). The IG was exposed to a combined training with traditional exercise and exergaming, twice a week over a period of 12 weeks. The CG performed only traditional sessions. CF was assessed by the Cognitive Telephone Screening Instrument. The time points for assessment were at zero (pretest), 12 (posttest), and 17 weeks (follow-up). RESULTS: Active CG and IG increased from pretest to posttest in short-term memory (STM), long-term memory (LTM), and Cognitive Telephone Screening Instrument total score 1.98 > Z < 3.00, ps < .005, with moderately large positive effects (.36 > r < .54). A significant increase was seen from posttest to follow-up in STM, Z = 2.74, p = .006, and LTM, Z = 2.31, p < .021, only in IG. Across the two time periods posttest to follow-up, there were significant interaction effects between program type and time for STM (p = .022, ηp2=.17) and LTM (p = .004, ηp2=.25), demonstrating a more beneficial effect of the exergames intervention compared to the CG. Discussion and Implications: The integration of exergaming in a multicomponent functional fitness exercise might have the potential to maintain and improve CF (in particular, STM and LTM) in older adults.

Ecological Momentary Assessment in Behavioral Research: Addressing Technological and Human Participant Challenges.

BACKGROUND: Ecological momentary assessment (EMA) assesses individuals' current experiences, behaviors, and moods as they occur in real time and in their natural environment. EMA studies, particularly those of longer duration, are complex and require an infrastructure to support the data flow and monitoring of EMA completion. OBJECTIVE: Our objective is to provide a practical guide to developing and implementing an EMA study, with a focus on the methods and logistics of conducting such a study. METHODS: The EMPOWER study was a 12-month study that used EMA to examine the triggers of lapses and relapse following intentional weight loss. We report on several studies that informed the implementation of the EMPOWER study: (1) a series of pilot studies, (2) the EMPOWER study's infrastructure, (3) training of study participants in use of smartphones and the EMA protocol and, (4) strategies used to enhance adherence to completing EMA surveys. RESULTS: The study enrolled 151 adults and had 87.4% (132/151) retention rate at 12 months. Our learning experiences in the development of the infrastructure to support EMA assessments for the 12-month study spanned several topic areas. Included were the optimal frequency of EMA prompts to maximize data collection without overburdening participants; the timing and scheduling of EMA prompts; technological lessons to support a longitudinal study, such as proper communication between the Android smartphone, the Web server, and the database server; and use of a phone that provided access to the system's functionality for EMA data collection to avoid loss of data and minimize the impact of loss of network connectivity. These were especially important in a 1-year study with participants who might travel. It also protected the data collection from any server-side failure. Regular monitoring of participants' response to EMA prompts was critical, so we built in incentives to enhance completion of EMA surveys. During the first 6 months of the 12-month study interval, adherence to completing EMA surveys was high, with 88.3% (66,978/75,888) completion of random assessments and around 90% (23,411/25,929 and 23,343/26,010) completion of time-contingent assessments, despite the duration of EMA data collection and challenges with implementation. CONCLUSIONS: This work informed us of the necessary preliminary steps to plan and prepare a longitudinal study using smartphone technology and the critical elements to ensure participant engagement in the potentially burdensome protocol, which spanned 12 months. While this was a technology-supported and -programmed study, it required close oversight to ensure all elements were functioning correctly, particularly once human participants became involved.

Coaching or gaming? Implications of strategy choice for home based stroke rehabilitation.

BACKGROUND: The enduring aging of the world population and prospective increase of age-related chronic diseases urge the implementation of new models for healthcare delivery. One strategy relies on ICT (Information and Communications Technology) home-based solutions allowing clients to pursue their treatments without institutionalization. Stroke survivors are a particular population that could strongly benefit from such solutions, but is not yet clear what the best approach is for bringing forth an adequate and sustainable usage of home-based rehabilitation systems. Here we explore two possible approaches: coaching and gaming. METHODS: We performed trials with 20 healthy participants and 5 chronic stroke survivors to study and compare execution of an elbow flexion and extension task when performed within a coaching mode that provides encouragement or within a gaming mode. For each mode we analyzed compliance, arm movement kinematics and task scores. In addition, we assessed the usability and acceptance of the proposed modes through a customized self-report questionnaire. RESULTS: In the healthy participants sample, 13/20 preferred the gaming mode and rated it as being significantly more fun (p < .05), but the feedback delivered by the coaching mode was subjectively perceived as being more useful (p < .01). In addition, the activity level (number of repetitions and total movement of the end effector) was significantly higher (p < .001) during coaching. However, the quality of movements was superior in gaming with a trend towards shorter movement duration (p = .074), significantly shorter travel distance (p < .001), higher movement efficiency (p < .001) and higher performance scores (p < .001). Stroke survivors also showed a trend towards higher activity levels in coaching, but with more movement quality during gaming. Finally, both training modes showed overall high acceptance. CONCLUSIONS: Gaming led to higher enjoyment and increased quality in movement execution in healthy participants. However, we observed that game mechanics strongly determined user behavior and limited activity levels. In contrast, coaching generated higher activity levels. Hence, the purpose of treatment and profile of end-users has to be considered when deciding on the most adequate approach for home based stroke rehabilitation.

iPod-based in-home system for monitoring gaze-stabilization exercise compliance of individuals with vestibular hypofunction.

BACKGROUND: In the physical therapy setting, physical therapists (PTs) often prescribe exercises for their clients to perform at home. However, it is difficult for PTs to obtain information about their clients' compliance with the prescribed exercises, the quality of performance and symptom magnitude. We present an iPod-based system for capturing this information from individuals with vestibular hypofunction while they perform gaze stabilization exercises at home. METHOD: The system's accuracy for measurement of rotational velocity against an independent motion tracker was validated. Then a seven day in-home trial was conducted with 10 individuals to assess the feasibility of implementing the system. Compliance was measured by comparing the recorded frequency and duration of the exercises with the exercise prescription. The velocity and range of motion of head movements was recorded in the pitch and yaw planes. The system also recorded dizziness severity before and after each exercise was performed. Each patient was interviewed briefly after the trial to ascertain ease of use. In addition, an interview was performed with PTs in order to assess how the information would be utilized. RESULTS: The correlation of the velocity measurements between the iPod-based system and the motion tracker was 0.99. Half of the subjects were under-compliant with the prescribed exercises. The average head velocity during performance was 140 deg/s in the yaw plane and 101 deg/s in the pitch plane. CONCLUSIONS: The iPod-based system was able to be used in-home. Interviews with PTs suggest that the quantitative data from the system will be valuable for assisting PTs in understanding exercise performance of patients, documenting progress, making treatment decisions, and communicating patient status to other PTs.

Designing the community multi-user health kiosk.

This paper discusses the design and development of a multi-user health kiosk intended for independent use by underserved populations. The modular integration of physiological sensors and psycho-social assessments provides an extensible, customizable platform for research. We present the development of the kiosk's feature set and user interaction mechanisms through iterative user testing, in addition to some technical challenges and solutions resulting from our design choices.

Skeleton Tracking Solutions for a Low-Cost Stroke Rehabilitation Support System.

Computer systems based on motion assessment are promising solutions to support stroke survivors' autonomous rehabilitation exercises. In this regard, researchers keep trying to achieve engaging and low-cost solutions suitable mainly for home use. Aiming to achieve a system with a minimal technical setup, we compare Microsoft Kinect, OpenPose, and MediaPipe skeleton tracking approaches for upper extremity quality of movement assessment after stroke. We determine if classification models assess accurately exercise performance with OpenPose and MediaPipe data against Kinect, using a dataset of 15 stroke survivors. We compute Root Mean Squared Error to determine the alignment of trajectories and kinematic variables. MediaPipe World Landmarks revealed high alignment with Kinect, revealing to be a potential alternative method.

Design, development, and evaluation of an interactive personalized social robot to monitor and coach post-stroke rehabilitation exercises.

Socially assistive robots are increasingly being explored to improve the engagement of older adults and people with disability in health and well-being-related exercises. However, even if people have various physical conditions, most prior work on social robot exercise coaching systems has utilized generic, predefined feedback. The deployment of these systems still remains a challenge. In this paper, we present our work of iteratively engaging therapists and post-stroke survivors to design, develop, and evaluate a social robot exercise coaching system for personalized rehabilitation. Through interviews with therapists, we designed how this system interacts with the user and then developed an interactive social robot exercise coaching system. This system integrates a neural network model with a rule-based model to automatically monitor and assess patients' rehabilitation exercises and can be tuned with individual patient's data to generate real-time, personalized corrective feedback for improvement. With the dataset of rehabilitation exercises from 15 post-stroke survivors, we demonstrated our system significantly improves its performance to assess patients' exercises while tuning with held-out patient's data. In addition, our real-world evaluation study showed that our system can adapt to new participants and achieved 0.81 average performance to assess their exercises, which is comparable to the experts' agreement level. We further discuss the potential benefits and limitations of our system in practice.

The SMARTER pilot study: Testing feasibility of real-time feedback for dietary self-monitoring.

Self-monitoring (SM) of food intake is central to weight loss treatment. Technology makes it possible to reinforce this behavior change strategy by providing real-time feedback (FB) tailored to the diary entry. To test the feasibility of providing 1-4 daily FB messages tailored to dietary recordings via a smartphone, we conducted a 12-week pilot randomized clinical trial in Pittsburgh, PA in US in 2015. We compared 3 groups: SM using the Lose It! smartphone app (Group 1); SM + FB (Group 2); and SM + FB + attending three in-person group sessions (Group 3). The sample (N = 39) was mostly white and female with a mean body mass index of 33.76 kg/m2. Adherence to dietary SM was recorded daily, weight was assessed at baseline and 12 weeks. The mean percentage of days adherent to dietary SM was similar among Groups 1, 2, and 3 (p = 0.66) at 53.50% vs. 55.86% vs. 65.33%, respectively. At 12 weeks, all groups had a significant percent weight loss (p < 0.05), with no differences among groups (- 2.85% vs. - 3.14% vs. - 3.37%) (p = 0.95); 26% of the participants lost ≥ 5% of their baseline weight. Mean retention was 74% with no differences among groups (p = 0.37). All groups adhered to SM at levels comparable to or better than other weight loss studies and lost acceptable amounts of weight, with minimal intervention contact over 12 weeks. These preliminary findings suggest this 3-group approach testing SM alone vs. SM with real-time FB messages alone or supplemented with limited in-person group sessions warrants further testing in a larger, more diverse sample and for a longer intervention period.

An Adaptive Filter for the Removal of Drifting Sinusoidal Noise Without a Reference.

This paper presents a method for filtering sinusoidal noise with a variable bandwidth filter that is capable of tracking a sinusoid's drifting frequency. The method, which is based on the adaptive noise canceling (ANC) technique, will be referred to here as the adaptive sinusoid canceler (ASC). The ASC eliminates sinusoidal contamination by tracking its frequency and achieving a narrower bandwidth than typical notch filters. The detected frequency is used to digitally generate an internal reference instead of relying on an external one as ANC filters typically do. The filter's bandwidth adjusts to achieve faster and more accurate convergence. In this paper, the focus of the discussion and the data is physiological signals, specifically electrocorticographic (ECoG) neural data contaminated with power line noise, but the presented technique could be applicable to other recordings as well. On simulated data, the ASC was able to reliably track the noise's frequency, properly adjust its bandwidth, and outperform comparative methods including standard notch filters and an adaptive line enhancer. These results were reinforced by visual results obtained from real ECoG data. The ASC showed that it could be an effective method for increasing signal to noise ratio in the presence of drifting sinusoidal noise, which is of significant interest for biomedical applications.

Serious Games for Home-based Stroke Rehabilitation.

On average, two thousand residents in the United States experience a stroke every day. These circumstances account for $28 billion direct costs annually and given the latest predictions, these costs will more than triple by 2030. In our research, we propose a portfolio of serious games for home-based stroke rehabilitation. The objective of the game approach is to enrich the training experience and establish a higher level of compliance to prescribed exercises, while maintaining a supportive training environment as found in common therapy sessions. Our system provides a collection of mini games based on rehabilitation exercises used in conventional physical therapy, monitors the patient's performance while exercising and provides clinicians with an interface to personalize the training. The clinician can set the current state of rehabilitation and change the playable games over time to drive diversification. While the system still has to be evaluated, an early stage case study with one patient offered positive indications towards this concept.

Usability testing of a prototype multi-user telehealth kiosk.

The overall purpose of this study was to learn how community-dwelling older adults would interact with our prototype multi-user telehealth kiosk and their views about its usability. Seven subjects participated in laboratory-based usability sessions to evaluate the physical design, appearance, functionality and perceived ease of use of a multi-user telehealth kiosk prototype. During usability testing participants recommended 18 new features (29% of comments), identified 15 software errors (23% of comments) and 29 user interface errors (47% of comments).

Automated filtering of common-mode artifacts in multichannel physiological recordings.

The removal of spatially correlated noise is an important step in processing multichannel recordings. Here, a technique termed the adaptive common average reference (ACAR) is presented as an effective and simple method for removing this noise. The ACAR is based on a combination of the well-known common average reference (CAR) and an adaptive noise canceling (ANC) filter. In a convergent process, the CAR provides a reference to an ANC filter, which in turn provides feedback to enhance the CAR. This method was effective on both simulated and real data, outperforming the standard CAR when the amplitude or polarity of the noise changes across channels. In many cases, the ACAR even outperformed independent component analysis. On 16 channels of simulated data, the ACAR was able to attenuate up to approximately 290 dB of noise and could improve signal quality if the original SNR was as high as 5 dB. With an original SNR of 0 dB, the ACAR improved signal quality with only two data channels and performance improved as the number of channels increased. It also performed well under many different conditions for the structure of the noise and signals. Analysis of contaminated electrocorticographic recordings further showed the effectiveness of the ACAR.

Sparse linear regression with elastic net regularization for brain-computer interfaces.

This paper demonstrates the feasibility of decoding neuronal population signals using a sparse linear regression model with an elastic net penalty. In offline analysis of real electrocorticographic (ECoG) neural data the elastic net achieved a timepoint decoding accuracy of 95% for classifying hand grasps vs. rest, and 82% for moving a cursor in 1-D space towards a target. These results were superior to those obtained using ℓ(2)-penalized and unpenalized linear regression, and marginally better than ℓ(1)-penalized regression. Elastic net and the ℓ(1)-penalty also produced sparse feature sets, but the elastic net did not eliminate correlated features, which could result in a more stable decoder for brain-computer interfaces.

Fully automated reduction of ocular artifacts in high-dimensional neural data.

The reduction of artifacts in neural data is a key element in improving analysis of brain recordings and the development of effective brain-computer interfaces. This complex problem becomes even more difficult as the number of channels in the neural recording is increased. Here, new techniques based on wavelet thresholding and independent component analysis (ICA) are developed for use in high-dimensional neural data. The wavelet technique uses a discrete wavelet transform with a Haar basis function to localize artifacts in both time and frequency before removing them with thresholding. Wavelet decomposition level is automatically selected based on the smoothness of artifactual wavelet approximation coefficients. The ICA method separates the signal into independent components, detects artifactual components by measuring the offset between the mean and median of each component, and then removing the correct number of components based on the aforementioned offset and the power of the reconstructed signal. A quantitative method for evaluating these techniques is also presented. Through this evaluation, the novel adaptation of wavelet thresholding is shown to produce superior reduction of ocular artifacts when compared to regression, principal component analysis, and ICA.

Frequency tracking and variable bandwidth for line noise filtering without a reference.

This paper presents a method for filtering line noise using an adaptive noise canceling (ANC) technique. This method effectively eliminates the sinusoidal contamination while achieving a narrower bandwidth than typical notch filters and without relying on the availability of a noise reference signal as ANC methods normally do. A sinusoidal reference is instead digitally generated and the filter efficiently tracks the power line frequency, which drifts around a known value. The filter's learning rate is also automatically adjusted to achieve faster and more accurate convergence and to control the filter's bandwidth. In this paper the focus of the discussion and the data will be electrocorticographic (ECoG) neural signals, but the presented technique is applicable to other recordings.

Virtual coach technology for supporting self-care.

"Virtual Coach" refers to a coaching program or device aiming to guide users through tasks for the purpose of prompting positive behavior or assisting with learning new skills. This article reviews virtual coach interventions with the purpose of guiding rehabilitation professionals to comprehend more effectively the essential components of such interventions, the underlying technologies and their integration, and example applications. A design space of virtual coach interventions including self-monitoring, context awareness, interface modality, and coaching strategies were identified and discussed to address when, how, and what coaching messages to deliver in an automated and intelligent way. Example applications that address various health-related issues also are provided to illustrate how a virtual coach intervention is developed and evaluated. Finally, the article provides some insight into addressing key challenges and opportunities in designing and implementing virtual coach interventions. It is expected that more virtual coach interventions will be developed in the field of rehabilitation to support self-care and prevent secondary conditions in individuals with disabilities.