A qualitative exploration of the experiences of transdermal alcohol sensor devices amongst people in receipt of treatment for alcohol use disorder

Introduction

Transdermal alcohol sensors (TAS) have the potential to be used as a clinical tool in alcohol treatment, but there is limited research with individuals with alcohol dependence using TAS. Our study is a qualitative evaluation of the views of people attending alcohol treatment and their experiences of wearing the BACtrack Skyn, within alcohol services in South London.

Methods

Participants with alcohol dependence wore a BACtrack Skyn TAS for one week and met with the researcher every two days, for a total of four meetings (for example: Monday, Wednesday, Friday, and Monday). In the final meeting, a post-wear survey (on their physical, social and comfort experience of the TAS) and semi-structured interview were completed. The Technology Acceptance Model (TAM) informed the topic guide and data analysis.

Results

Adults (N = 16) receiving alcohol treatment were recruited. Three core topics guided analysis: perceived usefulness, perceived ease of use and attitudes towards use. Participants found the TAS easy to wear and felt positive about its appearance and comfort. The only challenges reported were side effects, mostly skin irritation. The main two perceived uses were 1) TAS working as a drinking deterrent and 2) reducing daily breathalyser visits during detox.

Conclusion

Findings support the use of TAS amongst alcohol service users. Wearing the TAS for one week was acceptable and feasible for objective alcohol concentration measurement. Participants reported high perceived ease of use and usefulness of the Skyn in the context of alcohol treatment. These results are encouraging for the use of TAS in clinical settings.

Comparing self-reported energy intake using an online dietary tool with energy expenditure by an activity tracker

OBJECTIVE

The aim of this study was to compare self-reported total energy intake (TEI) collected using an online multiple-pass 24-h dietary recall tool (Intake24) with total energy expenditure (TEE) estimated from Fitbit Charge 2-improved algorithms in adults from the NoHoW trial (12-mo weight maintenance after free-living weight loss).

METHODS

Bland-Altman plots were used to assess the level of agreement between TEI and TEE at baseline and after 12 mo. The ratio of TEI to TEE was also calculated.

RESULTS

Data from 1323 participants (71% female) was included in the analysis (mean ± SD: age 45 ± 12 y, body mass index 29.7 ± 5.4 kg/m2, initial weight loss 11.5 ± 6.5 kg). The TEI was lower than TEE on average by 33%, with limits of agreement ranging from -91% to +25%. Men, younger individuals, those with higher body mass index, those with the greater weight loss before enrollment, and those who gained weight during the study underestimated to a greater extent.

CONCLUSIONS

These findings contribute to the ongoing research examining the validity of technology-based dietary assessment tools.

Precordial electrocardiographic recording and QT measurement from a novel wearable ring device

Background

The availability of portable and wearable electrocardiographic (ECG) devices has increased secondary to technological development. Single-lead ECG recordings have been shown to reliably detect and characterize cardiac rhythms such as atrial fibrillation. Acquisition of precordial electrodes for full 12-lead ECG reconstruction from bipolar recordings is complicated by the absence of a body ground/Wilson central terminal electrode. The extent of difference between standard precordial leads and those from a wearable bipolar ECG recorder has not been characterized.

Objective

The purpose of this study was to characterize the precordial ECG lead set from sequential bipolar recordings from an ECG ring wearable device.

Methods

In 70 patients who wore an ECG device on a right-hand finger, sequential precordial leads (CR1-CR6) were obtained along with chest electrodes (V1-V6). During acquisition of the modified precordial lead CR6, a full standardized 12-lead ECG capture was obtained. Signal quality was assessed using automated analysis software, and correlation values between the ring-derived ECG precordial leads and standard ECG leads were compared with regard to QRS duration, QT width, and RR interval.

Results

High concordance in the morphologies of precordial ECG leads obtained in a standard fashion and those recorded through an ECG ring was observed. Morphologic alignment improved with increasing laterality of the precordial lead with chest to right arm ring recording (CR5, CR6) compared with anterior chest leads to right arm (CR1, CR2). Segmental measurements of QRS duration and QT segment were well aligned and of high correlation.

Conclusion

Wearable ring-based ECG technology is capable of high-fidelity recordings of precordial leads for nonsimultaneous reconstruction of complete ECG sets. These recordings correlate highly with surface-obtained QRS and QT duration measurements and have significant implications for clinical applications. Uninterpretable tracings were primarily due to electrode noise from poor electrode contact.

"But for the blind spot": Accuracy and diagnostic performance of smart watch cardiac features in pediatric patients

BACKGROUND

The Apple Watch™ (AW) offers heart rate (HR) tracking by photoplethysmography (PPG) and single-lead electrocardiographic (ECG) recordings. The accuracy of AW-HR and diagnostic performance of AW-ECGs among children during both sinus rhythm and arrhythmias have not been explored.

OBJECTIVE

The purposes of this study were to assess the accuracy of AW-HR measurements compared to gold standard modalities in children during sinus rhythm and arrhythmias and to identify non-sinus rhythms using AW-ECGs.

METHODS

Subjects ≤18 years wore an AW during (1) telemetry admission, (2) electrophysiological study (EPS), or (3) exercise stress test (EST). AW-HRs were compared to gold standard modality values. Recorded AW-ECGs were reviewed by 3 blinded pediatric electrophysiologists.

RESULTS

Eighty subjects (median age 13 years; interquartile range 1.0-16.0 years; 50% female) wore AW (telemetry 41% [n = 33]; EPS 34% [n = 27]; EST 25% [n = 20]). A total of 1090 AW-HR measurements were compared to time-synchronized gold standard modality HR values. Intraclass correlation coefficient (ICC) was high 0.99 (0.98-0.99) for AW-HR during sinus rhythm compared to gold standard modalities. ICC was poor comparing AW-HR to gold standard modality HR in tachyarrhythmias (ICC 0.24-0.27) due to systematic undercounting of AW-HR values. A total of 126 AW-ECGs were reviewed. Identification of non-sinus rhythm by AW-ECG showed sensitivity of 89%-96% and specificity of 78%-87%.

CONCLUSIONS

We found high levels of agreement for AW-HR values with gold standard modalities during sinus rhythm and poor agreement during tachyarrhythmias, likely due to hemodynamic effects of tachyarrhythmias on PPG-based measurements. AW-ECGs had good sensitivity and moderate specificity in identification of non-sinus rhythm in children.

Upper limb assessment with inertial measurement units according to the international classification of functioning in stroke: a systematic review and correlation meta-analysis

OBJECTIVE

To investigate the usefulness of inertial measurement units (IMUs) in the assessment of motor function of the upper limb (UL) in accordance with the international classification of functioning (ICF).

DATA SOURCES

PubMed; Scopus; Embase; WoS and PEDro databases were searched from inception to 1 February 2022.

METHODS

The current systematic review follows PRISMA recommendations. Articles including IMU assessment of UL in stroke individuals have been included and divided into four ICF categories (b710, b735, b760, d445). We used correlation meta-analysis to pool the Fisher Z-score of each correlation between kinematics and clinical assessment.

RESULTS

A total of 35 articles, involving 475 patients, met the inclusion criteria. In the included studies, IMUs have been employed to assess the mobility of joint functions (n = 6), muscle tone functions (n = 4), control of voluntary movement functions (n = 15), and hand and arm use (n = 15). A significant correlation was found in overall meta-analysis based on 10 studies, involving 213 subjects: (r = 0.69) (95% CI: 0.69/0.98; p < 0.001) as in the d445 (r = 0.71) and b760 (r = 0.64) ICF domains, with no heterogeneity across the studies.

CONCLUSION

The literature supports the integration of IMUs and conventional clinical assessment in functional evaluation of the UL after a stroke. The use of a limited number of wearable sensors can provide additional kinematic features of UL in all investigated ICF domains, especially in the ADL tasks when a strong correlation with clinical evaluation was found.

A randomized controlled trial of Promoting Physical Activity in Regional and Remote Cancer Survivors (PPARCS)

BACKGROUND

Physical activity (PA) is important for cancer survivors. Trials of remotely delivered interventions are needed to assist in reaching under-served non-metropolitan cancer survivors. The objective of this study was to ascertain whether wearable technology, coupled with health coaching was effective in increasing PA in breast and colorectal cancer survivors living in regional and remote areas in Australia.

METHODS

Cancer survivors from 5 states were randomized to intervention and control arms. Intervention participants were given a Fitbit Charge 2TM and received up to 6 telephone health coaching sessions. Control participants received PA print materials. Accelerometer assessments at baseline and 12 weeks measured moderate-to-vigorous PA (MVPA), light PA, and sedentary behavior.

RESULTS

Eighty-seven participants were recruited (age = 63 ± 11 years; 74 (85%) female). There was a significant net improvement in MVPA of 49.8 min/week, favoring the intervention group (95% confidence interval (95%CI): 13.6-86.1, p = 0.007). There was also a net increase in MVPA bouts of 39.5 min/week (95%CI: 11.9-67.1, p = 0.005), favoring the intervention group. Both groups improved light PA and sedentary behavior, but there were no between-group differences.

CONCLUSION

This is the first study to demonstrate that, when compared to standard practice (i.e., PA education), a wearable technology intervention coupled with distance-based health coaching, improves MVPA in non-metropolitan cancer survivors. The results display promise for the use of scalable interventions using smart wearable technology in conjunction with phone-based health coaching to foster increased PA in geographically disadvantaged cancer survivors.

SmartWear body sensors for neurological and neurosurgical patients: A review of current and future technologies

Background/objective

Recent technological advances have allowed for the development of smart wearable devices (SmartWear) which can be used to monitor various aspects of patient healthcare. These devices provide clinicians with continuous biometric data collection for patients in both inpatient and outpatient settings. Although these devices have been widely used in fields such as cardiology and orthopedics, their use in the field of neurosurgery and neurology remains in its infancy.

Methods

A comprehensive literature search for the current and future applications of SmartWear devices in the above conditions was conducted, focusing on outpatient monitoring.

Findings

Through the integration of sensors which measure parameters such as physical activity, hemodynamic variables, and electrical conductivity - these devices have been applied to patient populations such as those at risk for stroke, suffering from epilepsy, with neurodegenerative disease, with spinal cord injury and/or recovering from neurosurgical procedures. Further, these devices are being tested in various clinical trials and there is a demonstrated interest in the development of new technologies.

Conclusion

This review provides an in-depth evaluation of the use of SmartWear in selected neurological diseases and neurosurgical applications. It is clear that these devices have demonstrated efficacy in a variety of neurological and neurosurgical applications, however challenges such as data privacy and management must be addressed.

From data to action: a scoping review of wearable technologies and biomechanical assessments informing injury prevention strategies in sport

BACKGROUND

The purpose of this scoping review was to evaluate the current use of technologies in sports settings for training adaptation and injury prevention. The review aimed to map the existing literature, identify key concepts and themes, and highlight gaps in research, thus offering guidance for future studies.

METHODS

This study followed the guidelines of the PRISMA extension for scoping reviews and a search in four major databases was conducted.

RESULTS

A total of 21 studies were included. The findings highlighted the widespread use of various technologies, including wearable devices and force plates, to monitor athletes' performance and inform evidence-based decision-making in training and injury prevention. Variables such as Player Load, changes of direction, and acute chronic workload ratio were identified as key metrics in injury prediction.

CONCLUSIONS

This review uncovers a dynamic field of research in athlete injury prevention, emphasizing the extensive use of varied technologies. A key finding is the pivotal role of Player Load data, which offers nuanced insights for customizing training loads according to sport-specific demands, player positions, and the physical requirements of various activities. Additionally, the review sheds light on the utility of tools like force plates in assessing fatigue, aiding recovery, and steering injury rehabilitation, particularly in sports prone to knee and ankle injuries. These insights not only enhance our understanding of injury prevention but also provide a strategic direction for future research, aiming to boost athlete safety, performance, and career longevity.

Behavioural digital biomarkers enable real-time monitoring of patient-reported outcomes: a substudy of the multicenter, prospective observational SafeHeart study

INTRODUCTION

Patient-reported outcome measures (PROMs) serve multiple purposes, including shared decision-making and patient communication, treatment monitoring and health-technology assessment. Patient monitoring using PROMs is constrained by recall and non-response bias, respondent burden and missing data. We evaluated the potential of behavioural digital biomarkers obtained from a wearable accelerometer to achieve personalised predictions of PROMs.

METHODS

Data from the multicenter, prospective SafeHeart study conducted at Amsterdam University Medical Center in the Netherlands and Copenhagen University Hospital, Rigshospitalet in Copenhagen, Denmark, was used. The study enrolled patients with an implantable cardioverter defibrillator (ICD) between May 2021 and September 2022 who then wore wearable devices with raw acceleration output to capture digital biomarkers reflecting physical behaviour. To collect PROMs, patients received the KCCQ and EQ5D-5 L questionnaire at two instances; baseline and after 6 months. Multivariable Tobit regression models were used to explore associations between digital biomarkers and PROMs, specifically whether digital biomarkers could enable PROM prediction.

RESULTS

The study population consisted of 303 patients (mean age 62.9 ± 10.9 years, 81.2% male). Digital biomarkers showed significant correlations to patient-reported physical and social limitations, severity and frequency of symptoms and quality of life. Prospective validation of the Tobit models indicated moderate correlations between the observed and predicted scores for KCCQ (concordance correlation coefficient (CCC) = 0.49, mean difference: 1.07 points) and EQ5D-5 L (CCC = 0.38, mean difference 0.02 points).

CONCLUSION

Wearable digital biomarkers correlate with PROMs, and may be leveraged for real-time prediction. These findings hold promise for monitoring of PROMs through wearable accelerometers.

Effects of Virtual Reality on Transtibial Amputation Rehabilitation Outcomes: A Randomized Study

Purpose: Virtual reality is widely used in patients with chronic musculoskeletal problems. However, the short-term effects on individuals with transtibial (TT) amputation during this process remain unclear. This study aimed at investigating the effects of virtual reality on rehabilitation outcomes in TT amputees. Methods: The study included 20 TT amputees who were using TT prostheses. The participants were divided into two groups randomly as follows: physiotherapy (PT) and virtual reality (VR). Participants were treated 3 days a week, for 4 weeks, and evaluations were made before and after treatment; a 6-minute walk test was used for performance, a single-leg balance test for balance, Trinity Amputation Prosthesis Experience Scale for prosthesis satisfaction, a 10-meter walking test for gait speed, and a wearable smart t-shirt to determine cadence. Results: It was found that there was a statistically significant difference in performance, balance, prosthesis satisfaction, cadence, and gait speed before and after PT (P < 0.05). There were differences in terms of performance, prosthesis satisfaction, balance, cadence, and gait speed before and after VR (P < 0.05). There was no statistically significant difference between PT and VR (P > 0.05). Conclusion: The 4 weeks of VR training improved performance, prosthesis satisfaction, balance, cadence, and gait speed in TT amputation rehabilitation similar to physiotherapy methods. The addition of VR training to amputation rehabilitation will bring improvements since it is a fun and safe intervention. Clinical Trial Registration: The trial is registered at Clinical Trials.gov, Trial No: NCT03872193.

A feasibility study to understand the components of behavioral sleep extension

Objectives

The goal of this study was to examine the contribution of sleep extension intervention components (wearable sleep tracker and coaching) on sleep extension outcomes.

Patient involvement

This study collected open ended qualitative responses of treatment preference, acceptability, and feasibility as a key outcome.

Methods

Adults aged 25 to 65 years with sleep duration <7 h and BMI ≥ 25 were randomized into one of four groups: Self-Management (control), Fitbit, Telephone Coaching, or Fitbit + Coaching. Self-report questionnaires and actigraphy were completed at baseline, post-intervention (6 weeks), and 12-weeks. Analyses used mixed models.

Results

Among the 38 adults randomized, the Fitbit + Coaching group had larger but non-significant improvements in sleep duration compared with the self-management group. The coaching group demonstrated significant improvements in sleep-related impairment. All groups demonstrated feasibility and acceptability but the Fitbit + Coaching group reported themes of accountability.

Conclusions

Results suggest that sleep extension interventions are feasible and acceptable but components affect the pattern of sleep and other outcomes.

Practical implications

Sleep extension is feasible and acceptable; the combination of coaching and the wearable device may lead to larger changes in sleep due to enhanced accountability.

Development and use of a porcine model with clinically relevant chronic infected wounds

Chronic ischemic wounds affect millions of people causing significant pain and disability. They can be considered to be stalled in the inflammatory stage and cannot heal without additional measures. A valid animal model is necessary to evaluate the efficacy of topical wound healing therapies and wearable technologies. A porcine model, although higher in cost, maintenance, and space requirements, is superior to the commonly used rodent or rabbit model for wound healing. Previous studies have shown that pig wounds have greater similarity to human wounds in responses to a variety of treatments, including wound dressings and antibiotics. The current study created a porcine model of large chronic wounds to assess a wearable electroceutical technology, with monitoring of healing variables and infection. Electroceutical therapy is the only adjunctive treatment recommended for chronic wound therapy. A porcine model of large chronic wounds of clinically realistic size was created and utilized to evaluate a wearable electroceutical biotechnology. Multivariate non-invasive assessment was used to monitor wound progression over multiple timepoints. Outcomes suggest that a wearable electrostimulation bandage, has the potential to offer therapeutic benefit in human wounds. The tested wearable device provides the same proven effectiveness of traditional electroceutical therapy while mitigating commonly cited barriers, including substantial time requirements, and availability and complexity of currently available equipment, preventing its implementation in routine wound care. The model is also appropriate for evaluation of other wearables or topical therapeutics.

Wearable technologies for health research: Opportunities, limitations, and practical and conceptual considerations

One of the most notable limitations of laboratory-based health research is its inability to continuously monitor health-relevant physiological processes as individuals go about their daily lives. As a result, we have generated large amounts of data with unknown generalizability to real-world situations and also created a schism between where data are collected (i.e., in the lab) and where we need to intervene to prevent disease (i.e., in the field). Devices using noninvasive wearable technology are changing all of this, however, with their ability to provide high-frequency assessments of peoples' ever-changing physiological states in daily life in a manner that is relatively noninvasive, affordable, and scalable. Here, we discuss critical points that every researcher should keep in mind when using these wearables in research, spanning device and metric decisions, hardware and software selection, and data quality and sampling rate issues, using research on stress and health as an example throughout. We also address usability and participant acceptability issues, and how wearable "digital biomarker" and behavioral data can be integrated to enhance basic science and intervention studies. Finally, we summarize 10 key questions that should be addressed to make every wearable study as strong as possible. Collectively, keeping these points in mind can improve our ability to study the psychobiology of human health, and to intervene, precisely where it matters most: in peoples' daily lives.

An Update on the Use of Wearable Devices in Men's Health

Men's health represents an often-overlooked aspect of public health. Men have higher mortality rates worldwide and are more negatively affected by chronic conditions such as obesity and heart disease, as well as addiction to alcohol and tobacco. Men also have health issues such as prostate cancer and male sexual dysfunction which only affect them. Because of the skewed burden of morbidity and mortality on men, it is imperative from a public health perspective to make a concerted effort to specifically improve men's health. The use of wearable devices in medical practice presents a novel avenue to invest in men's health in a safe, easily scalable, and economic fashion. Wearable devices are now ubiquitous in society, and their use in the healthcare setting is only increasing with time. There are commercially available devices such as smart watches which are available to lay people and healthcare professionals alike to improve overall health and wellness, and there are also purpose-built wearable devices which are used to track or treat a specific disease. In our review of the literature, we found that while research in the field of wearable devices is still in its early stages, there is ample evidence that wearable devices can greatly improve men's health in the long-term.

Depression deconstructed: Wearables and passive digital phenotyping for analyzing individual symptoms

Wearable technology enables unobtrusive collection of longitudinally dense data, allowing for continuous monitoring of physiology and behavior. These digital phenotypes, or device-based indicators, are frequently leveraged to study depression. However, they are usually considered alongside questionnaire sum-scores which collapse the symptomatic gamut into a general representation of severity. To explore the contributions of passive sensing streams more precisely, associations of nine passive sensing-derived features with self-report responses to Center for Epidemiologic Studies Depression (CES-D) items were modeled. Using data from the NetHealth study on N=469 college students, this work generated mixed ordinal logistic regression models to summarize contributions of pulse, movement, and sleep data to depression symptom detection. Emphasizing the importance of the college context, wearable features displayed unique and complementary properties in their heterogeneously significant associations with CES-D items. This work provides conceptual and exploratory blueprints for a reductionist approach to modeling depression within passive sensing research.

Wearable multisource quantitative gait analysis of Parkinson's diseases

As the motor symptoms of Parkinson's disease (PD) are complex and influenced by many factors, it is challenging to quantify gait abnormalities adequately using a single type of signal. Therefore, a wearable multisource gait monitoring system is developed to perform a quantitative analysis of gait abnormalities for improving the effectiveness of the clinical diagnosis. To detect multisource gait data for an accurate evaluation of gait abnormalities, force sensitive sensors, piezoelectric sensors, and inertial measurement units are integrated into the devised device. The modulation circuits and wireless framework are designed to simultaneously collect plantar pressure, dynamic deformation, and postural angle of the foot and then wirelessly transmit these collected data. With the designed system, multisource gait data from PD patients and healthy controls are collected. Multisource features for quantifying gait abnormalities are extracted and evaluated by a significance test of difference and correlation analysis. The results show that the features extracted from every single type of data are able to quantify the health status of the subjects (p < 0.001, ρ > 0.50). More importantly, the validity of multisource gait data is verified. The results demonstrate that the gait feature fusing multisource data achieves a maximum correlation coefficient of 0.831, a maximum Area Under Curve of 0.9206, and a maximum feature-based classification accuracy of 88.3%. The system proposed in this study can be applied to the gait analysis and objective evaluation of PD.

Digital measures of freezing of gait across the spectrum of normal, non-freezers, possible freezers and definite freezers

Over the course of the disease, freezing of gait (FoG) will gradually impact over 80% of people with Parkinson's disease (PD). Clinical decision-making and research design are often based on classification of patients as 'freezers' or 'non-freezers'. We derived an objective measure of FoG severity from inertial sensors on the legs to examine the continuum of FoG from absent to possible and severe in people with PD and in healthy controls. One hundred and forty-seven people with PD (Off-medication) and 83 healthy control subjects turned 360° in-place for 1 minute while wearing three wearable sensors used to calculate a novel Freezing Index. People with PD were classified as: 'definite freezers', new FoG questionnaire (NFOGQ) score > 0 and clinically observed FoG; 'non-freezers', NFOGQ = 0 and no clinically observed FoG; and 'possible freezers', either NFOGQ > 0 but no FoG observed or NFOGQ = 0 but FoG observed. Linear mixed models were used to investigate differences in participant characteristics among groups. The Freezing Index significantly increased from healthy controls to non-freezers to possible freezers and to definite freezers and showed, in average, excellent test-retest reliability (ICC = 0.89). Unlike the Freezing Index, sway, gait and turning impairments were similar across non-freezers, possible and definite freezers. The Freezing Index was significantly related to NFOG-Q, disease duration, severity, balance confidence, and the SCOPA-Cog (p < 0.01). An increase in the Freezing Index, objectively assessed with wearable sensors during a turning- in-place test, may help identify prodromal FoG in people with PD prior to clinically-observable or patient-perceived freezing. Future work should follow objective measures of FoG longitudinally.

Commercially available pressure sensors for sport and health applications: A comparative review

Pressure measurement systems have numerous applications in healthcare and sport. The purpose of this review is to: (a) describe the brief history of the development of pressure sensors for clinical and sport applications, (b) discuss the design requirements for pressure measurement systems for different applications, (c) critique the suitability, reliability, and validity of commercial pressure measurement systems, and (d) suggest future directions for the development of pressure measurements systems in this area. Commercial pressure measurement systems generally use capacitive or resistive sensors, and typically capacitive sensors have been reported to be more valid and reliable than resistive sensors for prolonged use. It is important to acknowledge, however, that the selection of sensors is contingent upon the specific application requirements. Recent improvements in sensor and wireless technology and computational power have resulted in systems that have higher sensor density and sampling frequency with improved usability - thinner, lighter platforms, some of which are wireless, and reduced the obtrusiveness of in-shoe systems due to wireless data transmission and smaller data-logger and control units. Future developments of pressure sensors should focus on the design of systems that can measure or accurately predict shear stresses in conjunction with pressure, as it is thought the combination of both contributes to the development of pressure ulcers and diabetic plantar ulcers. The focus for the development of in-shoe pressure measurement systems is to minimise any potential interference to the patient or athlete, and to reduce power consumption of the wireless systems to improve the battery life, so these systems can be used to monitor daily activity. A potential solution to reduce the obtrusiveness of in-shoe systems include thin flexible pressure sensors which can be incorporated into socks. Although some experimental systems are available further work is needed to improve their validity and reliability.

Cutaneous effects of photobiomodulation with 1072 nm light

Photobiomodulation, also known as low-level light therapy, has gained popularity in treating a variety of dermatologic and non-dermatologic conditions. The near-infrared (NIR) portion ranging from 700 to 1440 nm has a broad spectrum but most current research focuses on relatively shorter wavelengths. To date, clinical research regarding the application of 1072 NIR is limited to treatments for infections and photorejuvenation treatment in females. However, 1072 NIR light therapy may benefit male patients. This theoretical application is based on the biological properties of this subgroup having increased cutaneous density and thickness and the physical properties of 1072 NIR allowing it to penetrate increased depth. 1072 NIR can reach more cells throughout the epidermis and dermis compared to other parts of the electromagnetic spectrum traditionally used in phototherapy to provide unique and targeted benefits. 1072 NIR light-emitting diodes are commercially available and therefore hold tremendous potential to become accessible, affordable treatment options. Given the increased demand and market size for aesthetics for men that remains untapped, there is opportunity for future research to elucidate the potential for this wavelength as a safe and effective treatment.

Is Stryd critical power a meaningful parameter for runners?

Stryd is a foot pod that reliably estimates running power. Our objectives were to examine the efficacy of the website-generated Stryd critical power (CPSTRYD) as a meaningful parameter for runners. 20 runners performed their regular training while wearing Stryd for a minimum of 6 weeks to generate CPSTRYD. Runners completed laboratory graded exercise testing, and outdoor 1500 m and 5000 m time trails. CPSTRYD was most similar to the second ventilatory threshold (VT2) or the onset of blood lactate accumulation (OBLA) and is highly predictive of running performance. Stryd ground contact time (GCT) was a predictor of performance when comparing runners at the same submaximal treadmill speed. CPSTRYD generated from outdoor running is equivalent to that calculated using an established CP model. However, variance between different methods of CP estimation must be a consideration for runners and coaches. Stryd offers meaningful data for runners including a realistic estimate of CP.

The use of wireless sensors in the neonatal intensive care unit: a study protocol

Background

Continuous monitoring of vital signs and other biological signals in the Neonatal Intensive Care Unit (NICU) requires sensors connected to the bedside monitors by wires and cables. This monitoring system presents challenges such as risks for skin damage or infection, possibility of tangling around the patient body, or damage of the wires, which may complicate routine care. Furthermore, the presence of cables and wires can act as a barrier for parent-infant interactions and skin to skin contact. This study will investigate the use of a new wireless sensor for routine vital monitoring in the NICU.

Methods

Forty-eight neonates will be recruited from the Montreal Children's Hospital NICU. The primary outcome is to evaluate the feasibility, safety, and accuracy of a wireless monitoring technology called ANNE^® One (Sibel Health, Niles, MI, USA). The study will be conducted in 2 phases where physiological signals will be acquired from the standard monitoring system and the new wireless monitoring system simultaneously. In phase 1, participants will be monitored for 8 h, on four consecutive days, and the following signals will be obtained: heart rate, respiratory rate, oxygen saturation and skin temperature. In phase 2, the same signals will be recorded, but for a period of 96 consecutive hours. Safety and feasibility of the wireless devices will be assessed. Analyses of device accuracy and performance will be accomplished offline by the biomedical engineering team.

Conclusion

This study will evaluate feasibility, safety, and accuracy of a new wireless monitoring technology in neonates treated in the NICU.

Objective wearable measures and subjective questionnaires for predicting response to neurostimulation in people with chronic pain

BACKGROUND

Neurostimulation is an effective therapy for treating and management of refractory chronic pain. However, the complex nature of pain and infrequent in-clinic visits, determining subject's long-term response to the therapy remains difficult. Frequent measurement of pain in this population can help with early diagnosis, disease progression monitoring, and evaluating long-term therapeutic efficacy. This paper compares the utilization of the common subjective patient-reported outcomes with objective measures captured through a wearable device for predicting the response to neurostimulation therapy.

METHOD

Data is from the ongoing international prospective post-market REALITY clinical study, which collects long-term patient-reported outcomes from 557 subjects implanted by Spinal Cord Stimulator (SCS) or Dorsal Root Ganglia (DRG) neurostimulators. The REALITY sub-study was designed for collecting additional wearables data on a subset of 20 participants implanted with SCS devices for up to six months post implantation. We first implemented a combination of dimensionality reduction algorithms and correlation analyses to explore the mathematical relationships between objective wearable data and subjective patient-reported outcomes. We then developed machine learning models to predict therapy outcome based on the subject's response to the numerical rating scale (NRS) or patient global impression of change (PGIC).

RESULTS

Principal component analysis showed that psychological aspects of pain were associated with heart rate variability, while movement-related measures were strongly associated with patient-reported outcomes related to physical function and social role participation. Our machine learning models using objective wearable data predicted PGIC and NRS outcomes with high accuracy without subjective data. The prediction accuracy was higher for PGIC compared with the NRS using subjective-only measures primarily driven by the patient satisfaction feature. Similarly, the PGIC questions reflect an overall change since the study onset and could be a better predictor of long-term neurostimulation therapy outcome.

CONCLUSIONS

The significance of this study is to introduce a novel use of wearable data collected from a subset of patients to capture multi-dimensional aspects of pain and compare the prediction power with the subjective data from a larger data set. The discovery of pain digital biomarkers could result in a better understanding of the patient's response to therapy and their general well-being.

CORE™ wearable sensor: Comparison against gastrointestinal temperature during cold water ingestion and a 5 km running time-trial

Five km running time-trials (TT) are associated with rapid and significant increases in core body temperature (T_C). For such races, real-time feedback from pre-exercise and exercise T_C may be helpful in the design of an optimal pacing strategy aimed at limiting the possibility of developing heat-related illnesses. This study compared measurements of T_C obtained with a wearable device, the CORE™, to those of a gastrointestinal pill (GI pill), during cold water ingestion and a 5 km running TT. Twelve participants (25 ± 4 yrs) ingested 7.5 mL/kg fat-free mass of 4 °C water over the first 5 min of a 120 min sitting period, after which they completed a 5 km running TT at 30 °C, 50% relative humidity. A T_C difference > ± 0.25 °C between sensors was deemed clinically unacceptable. Prior to water ingestion, the CORE-derived T_C was 0.49 ± 0.25 °C lower than the GI pill. The CORE was irresponsive to the 0.26 ± 0.22 °C peak decline in T_C captured with the GI pill 40 min following water ingestion. Prior to the TT, T_C was 0.30 ± 0.25 °C lower with the CORE than the GI pill. During the TT, the CORE underestimated the rate of increase in T_C by 0.0125 ± 0.019 °C/min compared with the GI pill, and mean absolute difference in T_C between sensors was of 0.47 ± 0.34 °C. In conclusion, the CORE does not capture the cooling effect of cold water ingestion and provides a clinically relevant underestimation of T_C during a 5 km running TT in the heat.

Perspectives of users for a future interactive wearable system for upper extremity rehabilitation following stroke: a qualitative study

BACKGROUND

Wearable sensor technology can facilitate diagnostics and monitoring of people with upper extremity (UE) paresis after stroke. The purpose of this study is to investigate the perspectives of clinicians, people living with stroke, and their caregivers on an interactive wearable system that detects UE movements and provides feedback.

METHODS

This qualitative study used semi-structured interviews relating to the perspectives of a future interactive wearable system including a wearable sensor to capture UE movement and a user interface to provide feedback as the means of data collection. Ten rehabilitation therapists, 9 people with stroke, and 2 caregivers participated in this study.

RESULTS

Four themes were identified (1) "Everyone is different" highlighted the need for addressing individual user's rehabilitation goal and personal preference; (2) "The wearable system should identify UE and trunk movements" emphasized that in addition to arm, hand, and finger movements, detecting compensatory trunk movements during UE movements is also of interest; (3) "Both quality and amount of movements are necessary to measure" described the parameters related to how well and how much the user is using their affected UE that participants envisioned the system to monitor; (4) "Functional activities should be practiced by the users" outlined UE movements and activities that are of priority in designing the system.

CONCLUSIONS

Narratives from clinicians, people with stroke, and their caregivers offer insight into the design of interactive wearable systems. Future studies examining the experience and acceptability of existing wearable systems from end-users are warranted to guide the adoption of this technology.

Sensitivity and Specificity of Wearables for Atrial Fibrillation in Elderly Populations: A Systematic Review

PURPOSE OF REVIEW

This study aims to evaluate the sensitivity and specificity of wearable devices for AF detection in older adults, as well as examine the incidence of AF across various studies, contextual factors impacting AF detection, and safety and adverse events associated with wearable use.

RECENT FINDINGS

A systematic search of three databases identified 30 studies on wearables for AF detection in older adults, encompassing 111,798 participants. Both PPG-based and single-lead electrocardiography-based wearables show scalable potential for screening and managing AF. The results of this systematic review demonstrate that wearable devices, such as smartwatches, can effectively identify arrhythmias like AF in older adults, with scalable potential in PPG-based and single-lead electrocardiography-based wearables. As wearable technologies continue to gain prominence in healthcare, it is crucial to understand their challenges and incorporate them as preventative and monitoring tools for AF detection in elderly populations to improve patient care and prevention techniques.

Wireless monitoring devices in hospitalized children: a scoping review

The purpose of this study is to provide a structured overview of existing wireless monitoring technologies for hospitalized children. A systematic search of the literature published after 2010 was conducted in Medline, Embase, Scielo, Cochrane, and Web of Science. Two investigators independently reviewed articles to determine eligibility for inclusion. Information on study type, hospital setting, number of participants, use of a reference sensor, type and number of vital signs monitored, duration of monitoring, type of wireless information transfer, and outcomes of the wireless devices was extracted. A descriptive analysis was applied. Of the 1130 studies identified from our search, 42 met eligibility for subsequent analysis. Most included studies were observational studies with sample sizes of 50 or less published between 2019 and 2022. Common problems pertaining to study methodology and outcomes observed were short duration of monitoring, single focus on validity, and lack information on wireless transfer and data management.  Conclusion: Research on the use of wireless monitoring for children in hospitals has been increasing in recent years but often limited by methodological problems. More rigorous studies are necessary to establish the safety and accuracy of novel wireless monitoring devices in hospitalized children. What is Known: • Continuous monitoring of vital signs using wired sensors is the standard of care for hospitalized pediatric patients. However, the use of wires may pose significant challenges to optimal care. What is New: • Interest in wireless monitoring for hospitalized pediatric patients has been rapidly growing in recent years. • However, most devices are in early stages of clinical testing and are limited by inconsistent clinical and technological reporting.

Association of patient activity bio-profiles with health-related quality of life in patients with newly diagnosed multiple myeloma: a prospective observational cohort study

BACKGROUND

Due to the nature of their disease, patients with multiple myeloma (MM) often have bone disease-related pain that limits physical activity and diminishes health-related quality of life (HRQOL). Digital health technology with wearables and electronic patient reported outcome (ePRO) tools can provide insights into MM HRQoL.

METHODS

In this prospective observational cohort study conducted at Memorial Sloan Kettering Cancer in NY, NY, USA, patients with newly diagnosed MM (n = 40) in two cohorts (Cohort A - patients <65 years; Cohort B - patients ≥65 years) were passively remote-monitored for physical activity at baseline and continuously for up to 6 cycles of induction therapy from Feb 20, 2017 to Sep 10, 2019. The primary endpoint of the study was to determine feasibility of continuous data capture, defined as 13 or more patients of each 20-patient cohort compliant with capturing data for ≥16 h of a 24-hr period in ≥60% of days of ≥4 induction cycles. Secondary aims explored activity trends with treatment and association to ePRO outcomes. Patients completed ePRO surveys (EORTC - QLQC30 and MY20) at baseline and after each cycle. Associations between physical activity measurements, QLQC30 and MY20 scores, and time from the start of treatment were estimated using a linear mixed model with a random intercept.

FINDINGS

Forty patients were enrolled onto study, and activity bioprofiles were compiled among 24/40 (60%) wearable user participants (wearing the device for at least one cycle). In an intention to treat feasibility analysis, 21/40 (53%) patients [12/20 (60%) Cohort A; 9/20 (45%) Cohort B] had continuous data capture. Among data captured, overall activity trended upward cycle over cycle for the entire study cohort (+179 steps/24 h per cycle; p = 0.0014, 95% CI: 68-289). Older patients (age ≥65 years) had higher increases in activity (+260 steps/24 h per cycle; p < 0.0001, 95% CI: -154 to 366) compared to younger patients (+116 steps/24 h per cycle; p = 0.21, 95% CI: -60 to 293). Activity trends associated with improvement of ePRO domains, including physical functioning scores (p < 0.0001), global health scores (p = 0.02), and declining disease burden symptom scores (p = 0.042).

INTERPRETATION

Our study demonstrates that feasibility of passive wearable monitoring is challenging in a newly diagnosed MM patient population due to patient use. However, overall continuous data capture monitoring remains high among willing user participants. As therapy is initiated, we show improving activity trends, mainly in older patients, and that activity bioprofiles correlate with traditional HRQOL measurements.

FUNDING

Grants -National Institutes of HealthP30 CA 008748, Awards - Kroll Award 2019.

Age-related changes in gait biomechanics and their impact on the metabolic cost of walking: Report from a National Institute on Aging workshop

Changes in old age that contribute to the complex issue of an increased metabolic cost of walking (mass-specific energy cost per unit distance traveled) in older adults appear to center at least in part on changes in gait biomechanics. However, age-related changes in energy metabolism, neuromuscular function and connective tissue properties also likely contribute to this problem, of which the consequences are poor mobility and increased risk of inactivity-related disease and disability. The U.S. National Institute on Aging convened a workshop in September 2021 with an interdisciplinary group of scientists to address the gaps in research related to the mechanisms and consequences of changes in mobility in old age. The goal of the workshop was to identify promising ways to move the field forward toward improving gait performance, decreasing energy cost, and enhancing mobility for older adults. This report summarizes the workshop and brings multidisciplinary insight into the known and potential causes and consequences of age-related changes in gait biomechanics. We highlight how gait mechanics and energy cost change with aging, the potential neuromuscular mechanisms and role of connective tissue in these changes, and cutting-edge interventions and technologies that may be used to measure and improve gait and mobility in older adults. Key gaps in the literature that warrant targeted research in the future are identified and discussed.

The time cost of physiologically ineffective intravenous fluids in the emergency department: an observational pilot study employing wearable Doppler ultrasound

BACKGROUND

Little data exist on the time spent by emergency department (ED) personnel providing intravenous (IV) fluid to 'responsive' versus 'unresponsive' patients.

METHODS

A prospective, convenience sample of adult ED patients was studied; patients were enrolled if preload expansion was indicated for any reason. Using a novel, wireless, wearable ultrasound, carotid artery Doppler was obtained before and throughout a preload challenge (PC) prior to each bag of ordered IV fluid. The treating clinician was blinded to the results of the ultrasound. IV fluid was deemed 'effective' or 'ineffective' based on the greatest change in carotid artery corrected flow time (ccFT_∆) during the PC. The duration, in minutes, of each bag of IV fluid administered was recorded.

RESULTS

53 patients were recruited and 2 excluded for Doppler artifact. There were 86 total PCs included in the investigation comprising 81.7 L of administered IV fluid. 19,667 carotid Doppler cardiac cycles were analyzed. Using ccFT_∆ ≥  + 7 ms to discriminate 'physiologically effective' from 'ineffective' IV fluid, we observed that 54 PCs (63%) were 'effective', comprising 51.7 L of IV fluid, whereas, 32 (37%) were 'ineffective' comprising 30 L of IV fluid. 29.75 total hours across all 51 patients were spent in the ED providing IV fluids categorized as 'ineffective.'

CONCLUSIONS

We report the largest-known carotid artery Doppler analysis (i.e., roughly 20,000 cardiac cycles) in ED patients requiring IV fluid expansion. A clinically significant amount of time was spent providing physiologically ineffective IV fluid. This may represent an avenue to improve ED care efficiency.

Exploring Subtypes of Repetitive Behavior in Children with Autism Through Functional Analysis and Wearable Technology: a Pilot Biobehavioral Assessment

Objectives

Prior research has established assessment methodologies, such as functional analysis to identify specific contexts in which restricted and repetitive behavior (RRB) occurs, and measures of heart rate variability (HRV) to index the level of autonomic arousal in individuals with autism spectrum disorder (ASD). Yet, a gap remains in integrating multiple assessment methodologies to examine the complex underlying mechanisms of RRB. This study piloted a multi-disciplinary approach to assess both the functional behavioral and neurophysiological factors that may underlie occurrences of RRB. The study (a) evaluated the effect of a modified functional analysis protocol on delineating functional subtypes of RRB and (b) explored the effect of using a wearable technology within a functional analysis on identifying the relationship between RRB and HRV.

Method

A single-case alternating treatment design was used to randomly alternate noncontingent low-stimulation and high-stimulation conditions in a modified functional analysis protocol. Simultaneous measurement of RRB and HRV was obtained through direct behavioral observations and a wristband that collects blood volume pulse, respectively. Visual analysis of time series data was used to determine the functional subtypes of RRB, and nonparametric correlational analyses were conducted to determine the association between HRV and RRB.

Results

Findings from a sample of six participants suggest preliminary effectiveness of the assessment protocol in identifying subtypes of RRB and a significant correlation between HRV and RRB.

Conclusions

This study demonstrates the potential effect and usability of a wearable technology-aided biobehavioral approach to assess RRB and HRV in individuals with ASD.

Initial Development of User-Based Quality Evaluation Questionnaire of Smartwatch Technology for Applying to Healthcare

Background

Smartwatches are a consumer wearable device offering a potential, practical, and affordable method to collect personal health data in healthy adults. For patients with chronic diseases, this would enable symptom monitoring and aid clinical decision making. Therefore, providing customized checklists to recommend smartwatches is beneficial. However, few studies have evaluated the practical functions of smartwatches and their influence on user acceptance. We aimed at developing a reliable tool to assess the quality of smartwatches from the users' perspective.

Methods

To develop the smartwatch rating scale (SWRS), we conducted a comprehensive literature review as well as reviewed relevant websites. The SWRS includes 22 items for the usability (usability, functionality, safety, material, and display) and five items for the acceptance and adoption domain (satisfaction and intention). We measured the scale's internal consistency and inter-rater reliability by evaluating seven smartwatches.

Results

The overall scale demonstrated an excellent level of internal consistency (Cronbach's alpha = 0.91), with each subscale's internal consistency above good level (0.74 ~ 0.92). Inter-rater reliability using intraclass correlation coefficients (ICC) was at good level (2-way random ICC = 0.82, 95% CI 0.09 - 0.97).

Conclusions

The SWRS is reliable, which can meet the need for assessment of smartwatch technology for utilizing in personal healthcare. Accounting for users' perspectives will help make the most of technology without impairing the human aspects of care, this study can help consumers choose a smartwatch based on their preferences and provide guidelines for developing user-friendly wearable devices aimed at health behavior changes.

Quantifying training load and intensity in elite male ice hockey according to game-related contextual variables

We aimed to quantify training load (TL) and intensity during practice sessions according to game-related contextual variables (game outcome, opponent standard, game location) in an elite male ice hockey team. Practice data were collected using a wearable 200-Hz accelerometer, heart rate (HR) recording, and session-rating of perceived exertion (s-RPE) throughout 23 sessions (n = 306 files). The reference team performed a greater number of accelerations, decelerations, spent longer time > 85% maximum HR (t85%HR_max) and reported greater s-RPE after losing a game compared to a win (r = 0.13-0.19). Moreover, a lower number of accelerations, decelerations, t85%HR_max and s-RPE (r = 0.15-0.45) were found before playing against a top-ranked opponent. In contrast, more accelerations, decelerations, longer t85%HR_max and greater s-RPE were observed after playing against a top-ranked team opponent (r = 0.15-0.41). The players performed more accelerations/min, spent more t85%HR_max and reported greater s-RPE before playing an away game (r = 0.13-0.22). Weekly TL seems to slightly increase after losing a game, when preparing a game against a weaker opponent, after playing against a stronger opponent, and when preparing an away game. On the other hand, training intensity seems not to be affected by game-related contextual variables. Thus, ice hockey practitioners involved with TL monitoring should consider the interplay of the numerous variables that influence the volume of prescribed training and the actual training responses in each individual player.

Wearable technology in the sports medicine clinic to guide the return-to-play and performance protocols of athletes following a COVID-19 diagnosis

The coronavirus disease 2019 (COVID-19) pandemic has enabled the adoption of digital health platforms for self-monitoring and diagnosis. Notably, the pandemic has had profound effects on athletes and their ability to train and compete. Sporting organizations worldwide have reported a significant increase in injuries manifesting from changes in training regimens and match schedules resulting from extended quarantines. While current literature focuses on the use of wearable technology to monitor athlete workloads to guide training, there is a lack of literature suggesting how such technology can mediate the return to sport processes of athletes infected with COVID-19. This paper bridges this gap by providing recommendations to guide team physicians and athletic trainers on the utility of wearable technology for improving the well-being of athletes who may be asymptomatic, symptomatic, or tested negative but have had to quarantine due to a close exposure. We start by describing the physiologic changes that occur in athletes infected with COVID-19 with extended deconditioning from a musculoskeletal, psychological, cardiopulmonary, and thermoregulatory standpoint and review the evidence on how these athletes may safely return to play. We highlight opportunities for wearable technology to aid in the return-to-play process by offering a list of key parameters pertinent to the athlete affected by COVID-19. This paper provides the athletic community with a greater understanding of how wearable technology can be implemented in the rehabilitation process of these athletes and spurs opportunities for further innovations in wearables, digital health, and sports medicine to reduce injury burden in athletes of all ages.

A novel approach to quantify the assistive torque profiles generated by passive back-support exoskeletons

Industrial exoskeletons are a promising ergonomic intervention to reduce the risk of work-related musculoskeletal disorders by providing external physical support to workers. Passive exoskeletons, having no power supplies, are of particular interest given their predominance in the commercial market. Understanding the mechanical behavior of the torque generation mechanisms embedded in passive exoskeletons is, however, essential to determine the efficacy of these devices in reducing physical loads (e.g., in manual material handling tasks). We introduce a novel approach using a computerized dynamometer to quantify the assistive torque profiles of two passive back-support exoskeletons (BSEs) at different support settings and in both static and dynamic conditions. The feasibility of this approach was examined using both human subjects and a mannequin. Clear differences in assistive torque magnitudes were evident between the two BSEs, and both devices generated more assistive torques during trunk/hip flexion than extension. Assistive torques obtained from human subjects were often within similar ranges as those from the mannequin, though values were more comparable over a narrow range of flexion/extension angles due to practical limitations with the dynamometer and human subjects. Characterizing exoskeleton assistive torque profiles can help in better understanding how to select a torque profile for given task requirements and user anthropometry, and aid in predicting the potential impacts of exoskeleton use by incorporating measured torque profiles in a musculoskeletal modeling system. Future work is recommended to assess this approach for other occupational exoskeletons.

Automated estimation of ankle muscle EMG envelopes and resulting plantar-dorsi flexion torque from 64 garment-embedded electrodes uniformly distributed around the human leg

The design of personalized movement training and rehabilitation pipelines relies on the ability of assessing the activation of individual muscles concurrently with the resulting joint torques exerted during functional movements. Despite advances in motion capturing, force sensing and bio-electrical recording technologies, the estimation of muscle activation and resulting force still relies on lengthy experimental and computational procedures that are not clinically viable. This work proposes a wearable technology for the rapid, yet quantitative, assessment of musculoskeletal function. It comprises of (1) a soft leg garment sensorized with 64 uniformly distributed electromyography (EMG) electrodes, (2) an algorithm that automatically groups electrodes into seven muscle-specific clusters, and (3) a EMG-driven musculoskeletal model that estimates the resulting force and torque produced about the ankle joint sagittal plane. Our results show the ability of the proposed technology to automatically select a sub-set of muscle-specific electrodes that enabled accurate estimation of muscle excitations and resulting joint torques across a large range of biomechanically diverse movements, underlying different excitation patterns, in a group of eight healthy individuals. This may substantially decrease time needed for localization of muscle sites and electrode placement procedures, thereby facilitating applicability of EMG-driven modelling pipelines in standard clinical protocols.

Stroke Prevention in Atrial Fibrillation

PURPOSE OF REVIEW

Atrial fibrillation is associated with a significant increase in stroke and systemic embolism. This review explores the areas of stroke prevention.

RECENT FINDINGS

In the last decade, NOAC has overtaken warfarin as the anticoagulant of choice for stroke prevention in AF. For patients unable to take anticoagulation, LAA closure has proven to be a valid option. The use of digital devices has led to widespread consumer-directed AF screening. It remains to be determined if all device detect AF pose the same amount of risk as recent studies have shown that short and infrequent episodes of AF may not benefit from anticoagulation. Stroke prevention is paramount in the management of AF. In this review we describe the risk factors contributing to stroke, recent advances in antithrombotic therapies, and the increasing role of digital health in guiding AF detection and stroke prevention.

The mSteps pilot study: Analysis of the distance walked using a novel smartphone application in multiple sclerosis

BACKGROUND

Clinical studies in multiple sclerosis (MS) often require accurate measurement of walking distance. Utilisation of electronic devices could theoretically improve this. Mobile devices have the potential to continuously monitor health by collecting movement data. Popular fitness trackers record steps taken and distance travelled, typically using a fixed-stride length. However, applications using fixed-stride length may be less accurate in those with altered gait patterns. While useful for everyday purposes, medical monitoring requires greater accuracy.

OBJECTIVE

Our aim was to determine the agreement and reliability of using a smartphone application to measure distance walked.

METHOD

A phone application (mSteps) was developed and tested in a pilot study and then a validation study, looking at an indoor and outdoor setting with people with multiple sclerosis (PwMS) and a control cohort.

RESULTS

In the pilot study, the 95% limits of agreement (LOA) for outdoor tracking in control cohort lay within the a priori defined limit; however, the indoor tracking in both cohorts did not meet the defined limit. The app was then successfully validated outdoors in PwMS.

CONCLUSION

mSteps could be used to accurately measure distance outdoors in PwMS. There is still a need for solutions to accurately and reliably measure distance walked indoors.

Wearable Technology Leads to Initial Workup of Graves' Disease in an Adolescent Female

Graves' disease is the most common form of hyperthyroidism in the pediatric population. While the most prevalent symptoms seen in children with Graves' disease include goiter and excessive sweating (Minamitani et al., 2017), diagnosis is frequently delayed due to presentation with non-specific symptoms (Léger et al., 2018). This case report is of a 12-year-old female who presented to her pediatrician with a one month history of episodes of tachycardia both with physical exertion and at rest. Notably, these episodes were discovered on her electronic smartwatch by its heart rate monitoring feature. Further pertinent positives elicited in the patient's review of systems included increasing anxiety, diaphoresis, intermittent hand tremors, and recent weight loss. These findings led to further workup that included thyroid studies, culminating in a diagnosis of Graves' disease. Indeed, this patient's smartwatch aided in her initial presentation to her physician and allowed for prompt workup and diagnosis. There exist limited studies to date on the use of smartwatches to detect cardiac-related conditions in children, which may be due to the absence of Food and Drug Administration approval for certain cardiac-related smartwatch features in this patient population.

Asynchronous Veterinary Telemedicine

Asynchronous communication is the predominate modality for present day communication. Veterinarians can become more efficient and create more access to care if they incorporate more asynchronous care into daily practice. This article reviews how veterinary medicine has used asynchronous communication in the past, the advantages of asynchronous telemedicine, and the inclusion of the client in virtual referral.

Wearable technology for early detection of COVID-19: A systematic scoping review

Wearable technology is an emerging method for the early detection of coronavirus disease 2019 (COVID-19) infection. This scoping review explored the types, mechanisms, and accuracy of wearable technology for the early detection of COVID-19. This review was conducted according to the five-step framework of Arksey and O'Malley. Studies published between December 31, 2019 and December 15, 2021 were obtained from 10 electronic databases, namely, PubMed, Embase, Cochrane, CINAHL, PsycINFO, ProQuest, Scopus, Web of Science, IEEE Xplore, and Taylor & Francis Online. Grey literature, reference lists, and key journals were also searched. All types of articles describing wearable technology for the detection of COVID-19 infection were included. Two reviewers independently screened the articles against the eligibility criteria and extracted the data using a data charting form. A total of 40 articles were included in this review. There are 22 different types of wearable technology used to detect COVID-19 infections early in the existing literature and are categorized as smartwatches or fitness trackers (67%), medical devices (27%), or others (6%). Based on deviations in physiological characteristics, anomaly detection models that can detect COVID-19 infection early were built using artificial intelligence or statistical analysis techniques. Reported area-under-the-curve values ranged from 75% to 94.4%, and sensitivity and specificity values ranged from 36.5% to 100% and 73% to 95.3%, respectively. Further research is necessary to validate the effectiveness and clinical dependability of wearable technology before healthcare policymakers can mandate its use for remote surveillance.

Facilitators and barriers to real-life mobility in community-dwelling older adults: a narrative review of accelerometry- and global positioning system-based studies

Real-life mobility, also called "enacted" mobility, characterizes an individual's activity and participation in the community. Real-life mobility may be facilitated or hindered by a variety of factors, such as physical abilities, cognitive function, psychosocial aspects, and external environment characteristics. Advances in technology have allowed for objective quantification of real-life mobility using wearable sensors, specifically, accelerometry and global positioning systems (GPSs). In this review article, first, we summarize the common mobility measures extracted from accelerometry and GPS. Second, we summarize studies assessing the associations of facilitators and barriers influencing mobility of community-dwelling older adults with mobility measures from sensor technology. We found the most used accelerometry measures focus on the duration and intensity of activity in daily life. Gait quality measures, e.g., cadence, variability, and symmetry, are not usually included. GPS has been used to investigate mobility behavior, such as spatial and temporal measures of path traveled, location nodes traversed, and mode of transportation. Factors of note that facilitate/hinder community mobility were cognition and psychosocial influences. Fewer studies have included the influence of external environments, such as sidewalk quality, and socio-economic status in defining enacted mobility. Increasing our understanding of the facilitators and barriers to enacted mobility can inform wearable technology-enabled interventions targeted at delaying mobility-related disability and improving participation of older adults in the community.

Feasibility of the automatic ingestion monitor (AIM-2) for infant feeding assessment: a pilot study among breast-feeding mothers from Ghana

OBJECTIVE

Passive, wearable sensors can be used to obtain objective information in infant feeding, but their use has not been tested. Our objective was to compare assessment of infant feeding (frequency, duration and cues) by self-report and that of the Automatic Ingestion Monitor-2 (AIM-2).

DESIGN

A cross-sectional pilot study was conducted in Ghana. Mothers wore the AIM-2 on eyeglasses for 1 d during waking hours to assess infant feeding using images automatically captured by the device every 15 s. Feasibility was assessed using compliance with wearing the device. Infant feeding practices collected by the AIM-2 images were annotated by a trained evaluator and compared with maternal self-report via interviewer-administered questionnaire.

SETTING

Rural and urban communities in Ghana.

PARTICIPANTS

Participants were thirty eight (eighteen rural and twenty urban) breast-feeding mothers of infants (child age ≤7 months).

RESULTS

Twenty-five mothers reported exclusive breast-feeding, which was common among those < 30 years of age (n 15, 60 %) and those residing in urban communities (n 14, 70 %). Compliance with wearing the AIM-2 was high (83 % of wake-time), suggesting low user burden. Maternal report differed from the AIM-2 data, such that mothers reported higher mean breast-feeding frequency (eleven v. eight times, P = 0·041) and duration (18·5 v. 10 min, P = 0·007) during waking hours.

CONCLUSION

The AIM-2 was a feasible tool for the assessment of infant feeding among mothers in Ghana as a passive, objective method and identified overestimation of self-reported breast-feeding frequency and duration. Future studies using the AIM-2 are warranted to determine validity on a larger scale.

Adopting wearables to customize health insurance contributions: a ranking-type Delphi

Background

Wearables, as small portable computer systems worn on the body, can track user fitness and health data, which can be used to customize health insurance contributions individually. In particular, insured individuals with a healthy lifestyle can receive a reduction of their contributions to be paid. However, this potential is hardly used in practice.

Objective

This study aims to identify which barrier factors impede the usage of wearables for assessing individual risk scores for health insurances, despite its technological feasibility, and to rank these barriers according to their relevance.

Methods

To reach these goals, we conduct a ranking-type Delphi study with the following three stages. First, we collected possible barrier factors from a panel of 16 experts and consolidated them to a list of 11 barrier categories. Second, the panel was asked to rank them regarding their relevance. Third, to enhance the panel consensus, the ranking was revealed to the experts, who were then asked to re-rank the barriers.

Results

The results suggest that regulation is the most important barrier. Other relevant barriers are false or inaccurate measurements and application errors caused by the users. Additionally, insurers could lack the required technological competence to use the wearable data appropriately.

Conclusion

A wider use of wearables and health apps could be achieved through regulatory modifications, especially regarding privacy issues. Even after assuring stricter regulations, users’ privacy concerns could partly remain, if the data exchange between wearables manufacturers, health app providers, and health insurers does not become more transparent.

A proof of concept for continuous, non-invasive, free-living vital signs monitoring to predict readmission following an acute exacerbation of COPD: a prospective cohort study

Background

The use of vital signs monitoring in the early recognition of an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) post-hospital discharge is limited. This study investigated whether continuous vital signs monitoring could predict an AECOPD and readmission.

Methods

35 people were recruited at discharge following hospitalisation for an AECOPD. Participants were asked to wear an Equivital LifeMonitor during waking hours for 6 weeks and to complete the Exacerbations of Chronic Pulmonary Disease Tool (EXACT), a 14-item symptom diary, daily. The Equivital LifeMonitor recorded respiratory rate (RR), heart rate (HR), skin temperature (ST) and physical activity (PA) every 15-s. An AECOPD was classified as mild (by EXACT score), moderate (prescribed oral steroids/antibiotics) or severe (hospitalisation).

Results

Over the 6-week period, 31 participants provided vital signs and symptom data and 14 participants experienced an exacerbation, of which, 11 had sufficient data to predict an AECOPD. HR and PA were associated with EXACT score (p < 0.001). Three days prior to an exacerbation, RR increased by mean ± SD 2.0 ± 0.2 breaths/min for seven out of 11 exacerbations and HR increased by 8.1 ± 0.7 bpm for nine of these 11 exacerbations.

Conclusions

Increased heart rate and reduced physical activity were associated with worsening symptoms. Even with high-resolution data, the variation in vital signs data remains a challenge for predicting AECOPDs. Respiratory rate and heart rate should be further explored as potential predictors of an impending AECOPD.

Trial registration: ISRCTN registry; ISRCTN12855961. Registered 07 November 2018—Retrospectively registered, https://www.isrctn.com/ISRCTN12855961

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02018-5.

Wearable activity trackers-advanced technology or advanced marketing?

Wearable devices represent one of the most popular trends in health and fitness. Rapid advances in wearable technology present a dizzying display of possible functions: from thermometers and barometers, magnetometers and accelerometers, to oximeters and calorimeters. Consumers and practitioners utilize wearable devices to track outcomes, such as energy expenditure, training load, step count, and heart rate. While some rely on these devices in tandem with more established tools, others lean on wearable technology for health-related outcomes, such as heart rhythm analysis, peripheral oxygen saturation, sleep quality, and caloric expenditure. Given the increasing popularity of wearable devices for both recreation and health initiatives, understanding the strengths and limitations of these technologies is increasingly relevant. Need exists for continued evaluation of the efficacy of wearable devices to accurately and reliably measure purported outcomes. The purposes of this review are (1) to assess the current state of wearable devices using recent research on validity and reliability, (2) to describe existing gaps between physiology and technology, and (3) to offer expert interpretation for the lay and professional audience on how best to approach wearable technology and employ it in the pursuit of health and fitness. Current literature demonstrates inconsistent validity and reliability for various metrics, with algorithms not publicly available or lacking high-quality validation studies. Advancements in wearable technology should consider standardizing validation metrics, providing transparency in used algorithms, and improving how technology can be tailored to individuals. Until then, it is prudent to exercise caution when interpreting metrics reported from consumer-wearable devices.

Analysis and postprocessing of ECG or heart rate data from wearable devices beyond the proprietary cloud and app infrastructure of the vendors

Background

The impact of medical-grade wearable electrocardiographic (ECG) recording technology is increasing rapidly. A wide range of different portable smartphone-connected ECG and heart rate trackers is available on the market. Smart ECG devices are especially valuable to monitor either supraventricular arrhythmias or prolonged QT intervals to avoid drug-induced life-threatening arrhythmias. However, frequent false alarms or false-positive arrhythmia results from wearable devices are unwanted. Therefore, for clinical evaluation, it should be possible to measure and evaluate the biosignals of the wearables independent of the manufacturer.

Objective

Unlike radiological devices that do support the universal digital imaging and communications in medicine standard, these medical-grade devices do not yet support a secure standardized exchange pathway between sensors, smartphones/smartwatches, and end services such as cloud storage or universal Web-based application programming interface (API) access. Consequently, postprocessing of recorded ECGs or heart rate interval data requires a whole toolbox of customized software technologies.

Methods/Results

Various methods for measuring and analyzing nonstandardized ECG and heart rate data are proposed, including online measurement of ECG waveforms within a PDF, access to data using manufacturer-specific software development kits, and access to biosignals using modern Web APIs.

Conclusion

With the appropriate workaround, modern software technologies such as JavaScript and PHP allow health care providers and researchers to easily and instantly access necessary and important signal measurements on demand.

Using big data from long-form recordings to study development and optimize societal impact

Big data are everywhere. In this chapter, we focus on one source: long-form, child-centered recordings collected using wearable technologies. Because these recordings are simultaneously unobtrusive and encompassing, they may be a breakthrough technology for clinicians and researchers from several diverse fields. We demonstrate this possibility by outlining three applications for the recordings-clinical treatment, large-scale interventions, and language documentation-where we see the greatest potential. We argue that incorporating these recordings into basic and applied research will result in more equitable treatment of patients, more reliable measurements of the effects of interventions on real-world behavior, and deeper scientific insights with less observational bias. We conclude by outlining a proposal for a semistructured online platform where vast numbers of long-form recordings could be hosted and more representative, less biased algorithms could be trained.

Wearable electrochemical biosensors to measure biomarkers with complex blood-to-sweat partition such as proteins and hormones

Smart electronic devices based on micro-controllers, also referred to as fashion electronics, have raised wearable technology. These devices may process physiological information to facilitate the wearer's immediate biofeedback in close contact with the body surface. Standard market wearable devices detect observable features as gestures or skin conductivity. In contrast, the technology based on electrochemical biosensors requires a biomarker in close contact with both a biorecognition element and an electrode surface, where electron transfer phenomena occur. The noninvasiveness is pivotal for wearable technology; thus, one of the most common target tissues for real-time monitoring is the skin. Noninvasive biosensors formats may not be available for all analytes, such as several proteins and hormones, especially when devices are installed cutaneously to measure in the sweat. Processes like cutaneous transcytosis, the paracellular cell–cell unions, or even reuptake highly regulate the solutes content of the sweat. This review discusses recent advances on wearable devices based on electrochemical biosensors for biomarkers with a complex blood-to-sweat partition like proteins and some hormones, considering the commented release regulation mechanisms to the sweat. It highlights the challenges of wearable epidermal biosensors (WEBs) design and the possible solutions. Finally, it charts the path of future developments in the WEBs arena in converging/emerging digital technologies.

Wearable ultraviolet radiation sensors for research and personal use

Skin cancers are strongly linked to personal exposure to ultraviolet (UV) radiation, yet UV exposure is also the most preventable risk factor. People are exposed to UV rays when they engage in outdoor activities, particularly exercise, which is an important health behavior. Thus, researchers and the general public have shown increasing interest in measuring UV exposure using wearable sensors during outdoor physical activity. However, minimal research exists at the intersection of UV sensors, personal exposure, adaptive behavior due to exposures, and risk of skin damage. Recent years have seen an influx of new consumer-based and research-based UV-sensing technologies with wide-ranging form factors and purposes to fill this research gap, yet a thorough review of available sensors for specific purposes does not exist. Hence, the overall goal of this state-of-the-art review is to synthesize the current academic and gray literature surrounding personal UV-sensing technologies. Peer-reviewed journal articles and "gray literature," such as working papers, manuals, and UV sensor websites, were reviewed, assessing attributes of UV wearables marketed for research use, personal use, or both. Overall, 13 wearable UV sensors are available for personal use and/or research applications. These sensors vary from electronic to photochromic, with large differences in price, data outputs, accuracy, and precision. Recommendations are provided for which sensors are most suitable for various types of research or public use. Notably, the review findings will help guide researchers in future studies assessing UV exposure during physical activity.