Texting while walking differently alters gait patterns in people with multiple sclerosis and healthy individuals

Risk of using smartphones while walking for digital natives in realistic environments: Effects of cognitive-motor interference

The effect of using smartphones while walking on the cognitive and physical abilities of the "digital native" generation, i.e., individuals who have grown up in a digital media-centric environment, remains poorly understood. This study evaluated the effects of cognitive-motor interference on the use of smartphones while walking in children and young adults. The study involved 50 individuals from the digital age generation, including 24 children and 26 young adults. The study encompassed three experimental conditions, in which participants were instructed to traverse a distance of 60 m. The initial condition functioned as a control, wherein the participants walked without supplementary stimuli. In the second condition, the participants were provided with explicit instructions to grasp the smartphone device and position it in front of their chest by using both hands. This manipulation introduced a postural component into the experimental setup. The third condition required participants to be ambulatory while concurrently engaging in a cognitive task, namely, participating in a game that necessitated focused attention. Gait parameters were obtained by using inertial measurement unit sensors. Subsequently, the acquired gait characteristics were converted into dual-task costs (DTC). In the cognitive condition, children exhibited significantly greater DTC values for gait speed (76%), stride length (79%), stride time (102%), and stride length coefficient of variation (CV) than the young adults (p < 0.025). Moreover, as shown by the increased CV, a significant association exists between poor performance in smartphone games among children and increased variability in stride length. In children, the DTC of stride time CV decreased as smartphone game scores increased (R2 = 16.5%), and the DTC of stride length CV decreased more markedly as smartphone game scores increased (R2 = 28.2%). In conclusion, children are at a higher risk of pedestrian accidents when using smartphones while walking compared to young adults.

Innovative multidimensional gait evaluation using IMU in multiple sclerosis: introducing the semiogram

Background

Quantifying gait using inertial measurement units has gained increasing interest in recent years. Highly degraded gaits, especially in neurological impaired patients, challenge gait detection algorithms and require specific segmentation and analysis tools. Thus, the outcomes of these devices must be rigorously tested for both robustness and relevancy in order to recommend their routine use. In this study, we propose a multidimensional score to quantify and visualize gait, which can be used in neurological routine follow-up. We assessed the reliability and clinical coherence of this method in a group of severely disabled patients with progressive multiple sclerosis (pMS), who display highly degraded gait patterns, as well as in an age-matched healthy subjects (HS) group.

Methods

Twenty-two participants with pMS and nineteen HS were included in this 18-month longitudinal follow-up study. During the follow-up period, all participants completed a 10-meter walk test with a U-turn and back, twice at M0, M6, M12, and M18. Average speed and seven clinical criteria (sturdiness, springiness, steadiness, stability, smoothness, synchronization, and symmetry) were evaluated using 17 gait parameters selected from the literature. The variation of these parameters from HS values was combined to generate a multidimensional visual tool, referred to as a semiogram.

Results

For both cohorts, all criteria showed moderate to very high test-retest reliability for intra-session measurements. Inter-session quantification was also moderate to highly reliable for all criteria except smoothness, which was not reliable for HS participants. All partial scores, except for the stability score, differed between the two populations. All partial scores were correlated with an objective but not subjective quantification of gait severity in the pMS population. A deficit in the pyramidal tract was associated with altered scores in all criteria, whereas deficits in cerebellar, sensitive, bulbar, and cognitive deficits were associated with decreased scores in only a subset of gait criteria.

Conclusions

The proposed multidimensional gait quantification represents an innovative approach to monitoring gait disorders. It provides a reliable and informative biomarker for assessing the severity of gait impairments in individuals with pMS. Additionally, it holds the potential for discriminating between various underlying causes of gait alterations in pMS.

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

BACKGROUND

Wearable sensor technologies have the potential to improve monitoring in people with multiple sclerosis (MS) and inform timely disease management decisions. Evidence of the utility of wearable sensor technologies in people with MS is accumulating but is generally limited to specific subgroups of patients, clinical or laboratory settings, and functional domains.

OBJECTIVE

This review aims to provide a comprehensive overview of all studies that have used wearable sensors to assess, monitor, and quantify motor function in people with MS during daily activities or in a controlled laboratory setting and to shed light on the technological advances over the past decades.

METHODS

We systematically reviewed studies on wearable sensors to assess the motor performance of people with MS. We scanned PubMed, Scopus, Embase, and Web of Science databases until December 31, 2022, considering search terms "multiple sclerosis" and those associated with wearable technologies and included all studies assessing motor functions. The types of results from relevant studies were systematically mapped into 9 predefined categories (association with clinical scores or other measures; test-retest reliability; group differences, 3 types; responsiveness to change or intervention; and acceptability to study participants), and the reporting quality was determined through 9 questions. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines.

RESULTS

Of the 1251 identified publications, 308 were included: 176 (57.1%) in a real-world context, 107 (34.7%) in a laboratory context, and 25 (8.1%) in a mixed context. Most publications studied physical activity (196/308, 63.6%), followed by gait (81/308, 26.3%), dexterity or tremor (38/308, 12.3%), and balance (34/308, 11%). In the laboratory setting, outcome measures included (in addition to clinical severity scores) 2- and 6-minute walking tests, timed 25-foot walking test, timed up and go, stair climbing, balance tests, and finger-to-nose test, among others. The most popular anatomical landmarks for wearable placement were the waist, wrist, and lower back. Triaxial accelerometers were most commonly used (229/308, 74.4%). A surge in the number of sensors embedded in smartphones and smartwatches has been observed. Overall, the reporting quality was good.

CONCLUSIONS

Continuous monitoring with wearable sensors could optimize the management of people with MS, but some hurdles still exist to full clinical adoption of digital monitoring. Despite a possible publication bias and vast heterogeneity in the outcomes reported, our review provides an overview of the current literature on wearable sensor technologies used for people with MS and highlights shortcomings, such as the lack of harmonization, transparency in reporting methods and results, and limited data availability for the research community. These limitations need to be addressed for the growing implementation of wearable sensor technologies in clinical routine and clinical trials, which is of utmost importance for further progress in clinical research and daily management of people with MS.

TRIAL REGISTRATION

PROSPERO CRD42021243249; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=243249.

The effect of mobile phone task and age on gait: A systematic review and meta-analysis

Objective: Mobile phone usage while performing postural-locomotor tasks is everyday activity across persons of all ages in various environmental contexts and health conditions. However, it is also an important factor contributing to accidents. To lower the risk of pedestrian accidents, this meta-analysis aimed to examine how mobile phones affect pedestrian gait and identify how mobile phone tasks and participant age affect gait differently.

Methods: Electronic database searches were performed in The Cochrane Library, PubMed, and Medline. Two examiners evaluated the eligibility and quality of included studies using the Downs and Black checklist. The mean differences (MD) or standardized mean differences (SMD) were calculated for each outcome. Subgroup analyses were used to compare the differential effects of mobile phone task and participant age on gait.

Results: Among 22 eligible studies, 592 participants in 10 countries were analyzed in this meta-analysis. The overall meta-analysis showed that using a mobile phone significantly decreased pedestrian gait velocity (SMD = −1.45; 95% CI: −1.66 to −1.24; p &lt; 0.00001; I2 = 66%), step length (SMD = −1.01; 95% CI: −1.43 to −0.59; p &lt; 0.00001; I2 = 82%), and stride length (SMD = −0.9; 95% CI: −1.19 to −0.60; p &lt; 0.00001; I2 = 79%), significantly increased pedestrian step time (SMD = 0.77; 95% CI: 0.45 to 1.08; p &lt; 0.00001; I2 = 78%), stride time (SMD = 0.87; 95% CI: 0.69 to 1.06; p &lt; 0.00001; I2 = 24%), step width (SMD = 0.79; 95% CI: 0.34 to 1.24; p = 0.0006. I2 = 75%), double support time (SMD = 1.09; 95% CI: 0.86 to 1.31; p &lt; 0.00001; I2 = 42%), and double support (%gait cycle, %GC) (MD = 2.32; 95% CI: 1.75 to 2.88; p &lt; 0.00001; I2 = 26%).

Conclusion: In summary, the effects of mobile phone tasks and participant age on gait were inconsistent. Our study found that resource-intensive tasks (texting and reading) significantly reduced gait velocity, and step time; however, small resource-intensive tasks (calling, talking, and dialing) did not affect these outcomes. In contrast to young adults, step length and step time were not affected by mobile phone use in older adults. Tips: Pedestrians should consider using a mobile phone in their daily lives according to the application scenarios (walking environment, the complexity of mobile phone tasks, pedestrians’ task processing abilities, etc.) as appropriate to avoid dangerous accidents.

Systematic Review Registration: identifier CRD42022358963.

Does texting while walking affect spatiotemporal gait parameters in healthy adults, older people, and persons with motor or cognitive disorders? A systematic review and meta-analysis

BACKGROUND

Smartphone use during postural-locomotor tasks is an everyday activity for individuals of all ages in diverse environmental situations and with various health conditions. Nevertheless, the use of smartphones during walking is responsible for many accidents.

RESEARCH QUESTION

This systematic review and meta-analysis examined spatiotemporal gait parameters during the dual-task situation "texting + gait" versus isolated gait task (single task) in adult persons (>18 years).

METHODS

Electronic database searches were performed in PubMed, Embase, CINHAL, and LISSA. Two examiners assessed the eligibility and quality of appraisal with the Downs and Black checklist. The standardized mean difference (SMD) with 95 % confidence intervals was calculated to compare single- and dual-task situations. The pooled estimates of the overall effect were computed using a random or fixed effects method, and forest plots were generated.

RESULTS AND SIGNIFICANCE

A total of 25 studies were included. All studies included healthy adults, with four studies including older persons and three including people with pathological conditions. The walking task was with (N = 4) and without (N = 21) obstacles and in laboratory (N = 21) or ecological conditions (N = 7). The quality scores were 6-8/16 for eight studies, 9-12/16 for seven studies, and more than 12/16 for three studies. During the "texting + gait" tasks, the meta-analysis highlighted a significant impairment of gait speed, step and stride length, cadence, and double and single support (p < 0.05). The spatiotemporal parameters of gait were systematically altered during the texting task regardless of the population and test conditions. However, the quality of the studies is moderate, and few studies have been conducted for people with motor deficiencies. The impact of texting on walking should be better considered to develop prevention actions.

Risks of Accidents Caused by the Use of Smartphone by Pedestrians Are Task- and Environment-Dependent

Using smartphones during a task that requires an upright posture can be detrimental for the overall motor performance. The aim of this study was to determine the risks of accidents caused by the use of smartphones by pedestrians while walking in a controlled (laboratory) and a non-controlled (public street) environment. Two hundred and one participants, 100 men and 101 women, all young adults, were submitted to walking activities while texting messages and talking on the phone. The risk of accident was measured by the time and the number of steps necessary to walk a 20 ft distance. Assessments were performed with no external distractors (laboratory) and on a public street with vehicles, pedestrians, lights, and noises. Multivariate analysis of variance tests provided the main effect of task (using × not using smartphone), environment (laboratory × street), sex (men × women), and interactions. Significance was set at 5%. The results showed that using a smartphone while walking demanded a greater number of steps and time to perform the task (main effect of task: 0.84; p = 0.001). The risk of accident was higher on the streets where, due to traffic hazards, pedestrians performed the task faster and with a lower number of steps (the main effect of environment: 0.82; p = 0.001). There was no difference of risks between men and women (main effect of sex: 0.01; p = 0.225), whether in the laboratory or on the street (main effect of sex × environment: 0.01; p = 0.905). The task × environment interaction showed that using a smartphone on the street potentiates risks of accidents of pedestrians (main effect of task × environment: 0.41; p = 0.001). In conclusion, using a smartphone while walking can be risky for pedestrians, especially in a traffic environment. People should avoid using their smartphone while crossing streets.

The Impact of Using Mobile Phones on Gait Characteristics: A Narrative Review

The aim of this study was to summarize the research status and reveal the impact of mobile phone use on gait characteristics by reviewing the existing studies in terms of research status, participants, independent variables, dependent variables, main findings, etc. Twenty-nine studies which investigated the impact of using mobile phones on gait characteristics were identified through a literature search. The majority of these studies examined the effects of mobile phone use on gait characteristics in young people. The preliminary results showed that walking while using a mobile phone has significant impacts on gait. It can decrease gait velocity, cadence, step length and stride length, along with significantly increasing step width, step time and double support time. The results varied among different mobile phone usage, which resulted from the different motor and mental demands. Additionally, age and environment could affect the results as well. As well as the kinematic characteristics, we suggest that kinetic and EMG analysis are conducted in future studies.

Gait metrics analysis utilizing single-point inertial measurement units: a systematic review

BACKGROUND

Wearable sensors, particularly accelerometers alone or combined with gyroscopes and magnetometers in an inertial measurement unit (IMU), are a logical alternative for gait analysis. While issues with intrusive and complex sensor placement limit practicality of multi-point IMU systems, single-point IMUs could potentially maximize patient compliance and allow inconspicuous monitoring in daily-living. Therefore, this review aimed to examine the validity of single-point IMUs for gait metrics analysis and identify studies employing them for clinical applications.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines (PRISMA) were followed utilizing the following databases: PubMed; MEDLINE; EMBASE and Cochrane. Four databases were systematically searched to obtain relevant journal articles focusing on the measurement of gait metrics using single-point IMU sensors.

RESULTS

A total of 90 articles were selected for inclusion. Critical analysis of studies was conducted, and data collected included: sensor type(s); sensor placement; study aim(s); study conclusion(s); gait metrics and methods; and clinical application. Validation research primarily focuses on lower trunk sensors in healthy cohorts. Clinical applications focus on diagnosis and severity assessment, rehabilitation and intervention efficacy and delineating pathological subjects from healthy controls.

DISCUSSION

This review has demonstrated the validity of single-point IMUs for gait metrics analysis and their ability to assist in clinical scenarios. Further validation for continuous monitoring in daily living scenarios and performance in pathological cohorts is required before commercial and clinical uptake can be expected.

The patients' perspective on the perceived difficulties of dual-tasking: development and validation of the Dual-task Impact on Daily-living Activities Questionnaire (DIDA-Q)

BACKGROUND

Everyday-life activities often require performing dual tasks (DT), with consequent possible occurrence of motor-cognitive or motor-motor interference. This could reduce quality of life, in particular in people with neurological diseases. However, there is lack of validated tools to assess the patients' perspective on DT difficulties in this population. Therefore, we developed the Dual-task Impact on Daily-living Activities-Questionnaire (DIDA-Q) and tested its psychometric properties in people with multiple sclerosis (PwMS).

METHODS

Items were generated based on existing scales, DT paradigms used in previous studies and the opinion of a multi-stakeholder group, including both experts and PwMS. Twenty DT constituted the preliminary version of the DIDA-Q which was administered to 230 PwMS. The psychometric properties of the scale were evaluated including internal consistency, validity and reliability.

RESULTS

Nineteen items survived after exploratory factor analysis, showing a three-factor solution which identifies the components mostly contributing to DT perceived difficulty (i.e., balance and mobility, cognition and upper-limb ability). The DIDA-Q appropriately fits the graded response model, with first evaluations supporting internal consistency (Cronbach's alpha=0.95), validity (70% of the hypotheses for convergent and discriminant constructs confirmed) and reliability (intraclass correlation coefficients=0.95) of this tool.

CONCLUSION

The DIDA-Q could be used in research and clinical settings to discriminate individuals with low vs. high cognitive-motor or motor-motor interference, and to develop and evaluate the efficacy of personalized DT rehabilitative treatments in PwMS.

Effects of the use of mobile phone on postural and locomotor tasks: a scoping review

BACKGROUND

Using a mobile phone while performing a postural and locomotor tasks is a common, daily situation. Conversing or sending messages (SMS) while walking account for a significant share of accidental injuries. Therefore, understanding the consequences of using a mobile phone on balance and walking is important, all the more so when these postural and locomotor tasks are aggravated by a disease.

RESEARCH QUESTION

Our objective was to conduct a scoping review on the influence of a dual-task situation - generated by the use of mobile phone - on users' postural and/or locomotor tasks.

METHODS

The literature search was conducted in English on PubMed/Medline and CINHAL databases, using keywords associated with postural and locomotor tasks and with the use of mobile phone. Study location, population, number of subjects, experimental design, types of phone use, evaluated postural-locomotor tasks and expected effects were then analyzed.

RESULTS AND SIGNIFICANCE

46 studies were included in this work, 24 of which came from North America. All studies compared postural and locomotor tasks with and without the use of a smartphone. Ten studies also compared at least 2 groups with different characteristics. Only 4 studies included pathological subjects. Various modalities were tested, and most studies focused on walking. Results show that the use of smartphones slows down movement and induces a systematic imbalance, except when listening to music. The dual task of "using the smartphone during a postural or locomotor tasks" induces systematic disturbances of balance and movement, which must be taken into account in the rehabilitation approach. Future studies will have to extend the knowledge regarding pathological situations.

Comparing 16 Different Dual-Tasking Paradigms in Individuals With Multiple Sclerosis and Healthy Controls: Working Memory Tasks Indicate Cognitive-Motor Interference

Background: Cognitive–motor interference (CMI) is measured by dual-tasking (DT), which involves motor and cognitive tasks. There is no consensus as to whether CMI is present in multiple sclerosis (MS).

Objectives: We investigated the effects of 16 DT conditions by measuring motor complexity, cognitive domain, and task difficulty.

Method: In total, 40 persons with MS (pwMSs) with Expanded Disease Status Scale (EDSS) 3.2 ± 1.7 and 31 age- and sex-matched healthy controls (HCs) completed 2 single walking, 8 single cognitive, and 2 complex walking tasks and 16 cognitive–motor DT. The main outcomes were mean values of gait velocity and the percentage change from single to DT (motor DT costs, mDTCs) and mean values of cognitive task accuracy and the percentage changes (cognitive DTC, cDTC).

Results: Two-way analyses of variance showed the main effect of cognitive task yielded an F ratio of F_{(4, 268)} = 72.35, p < 0.01, for mean gait velocity, and an F ratio of F_{(4, 304)} = 17.12, p < 0.001, for mDTC, indicating that the mean velocity was significantly lower and the mDTC significantly higher for DS_B (mean = 1.27, SD = 0.03, and mean = 13.52, SD = 1.28, respectively). The main effect of cognitive task yielded an F ratio of F_{(4, 116)} = 84.32, p < 0.001, with the lowest average accuracy for DS_B (mean = 43.95, SD = 3.33); no effect was found for cDTC. In pwMSs, the EDSS accounted for 28% (F = 13.65, p = 0.001) of variance in a model predicting the highest mDTC.

Conclusions: Overall, among different cognitive tasks added, the Digit Span backward was the most interfering cognitive task over gait velocity and accuracy. The effect was similar independently from the motor complexity and the group. PwMSs and HCs behaved in a similar manner at all motor complexity levels and during all cognitive task.

Is a Wearable Sensor-Based Characterisation of Gait Robust Enough to Overcome Differences Between Measurement Protocols? A Multi-Centric Pragmatic Study in Patients with Multiple Sclerosis

Inertial measurement units (IMUs) allow accurate quantification of gait impairment of people with multiple sclerosis (pwMS). Nonetheless, it is not clear how IMU-based metrics might be influenced by pragmatic aspects associated with clinical translation of this approach, such as data collection settings and gait protocols. In this study, we hypothesised that these aspects do not significantly alter those characteristics of gait that are more related to quality and energetic efficiency and are quantifiable via acceleration related metrics, such as intensity, smoothness, stability, symmetry, and regularity. To test this hypothesis, we compared 33 IMU-based metrics extracted from data, retrospectively collected by two independent centres on two matched cohorts of pwMS. As a worst-case scenario, a walking test was performed in the two centres at a different speed along corridors of different lengths, using different IMU systems, which were also positioned differently. The results showed that the majority of the temporal metrics (9 out of 12) exhibited significant between-centre differences. Conversely, the between-centre differences in the gait quality metrics were small and comparable to those associated with a test-retest analysis under equivalent conditions. Therefore, the gait quality metrics are promising candidates for reliable multi-centric studies aiming at assessing rehabilitation interventions within a routine clinical context.