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Turning during walking is a relevant and common everyday movement and it depends on a correct top-down intersegmental coordination. This could be reduced in several conditions (en bloc turning), and an altered turning kinematics has been linked to increased risk of falls. Smartphone use has been associated with poorer balance and gait; however, its effect on turning-while-walking has not been investigated yet. This study explores turning intersegmental coordination during smartphone use in different age groups and neurologic conditions.
This study aims to evaluate the effect of smartphone use on turning behavior in healthy individuals of different ages and those with various neurological diseases.
Younger (aged 18-60 years) and older (aged >60 years) healthy individuals and those with Parkinson disease, multiple sclerosis, subacute stroke (<4 weeks), or lower-back pain performed turning-while-walking alone (single task [ST]) and while performing 2 different cognitive tasks of increasing complexity (dual task [DT]). The mobility task consisted of walking up and down a 5-m walkway at self-selected speed, thus including 180° turns. Cognitive tasks consisted of a simple reaction time test (simple DT [SDT]) and a numerical Stroop test (complex DT [CDT]). General (turn duration and the number of steps while turning), segmental (peak angular velocity), and intersegmental turning parameters (intersegmental turning onset latency and maximum intersegmental angle) were extracted for head, sternum, and pelvis using a motion capture system and a turning detection algorithm.
In total, 121 participants were enrolled. All participants, irrespective of age and neurologic disease, showed a reduced intersegmental turning onset latency and a reduced maximum intersegmental angle of both pelvis and sternum relative to head, thus indicating an en bloc turning behavior when using a smartphone. With regard to change from the ST to turning when using a smartphone, participants with Parkinson disease reduced their peak angular velocity the most, which was significantly different from lower-back pain relative to the head (
Smartphone use during turning-while-walking may lead to en bloc turning and thus increase fall risk across age and neurologic disease groups. This behavior is probably particularly dangerous for those groups with the most pronounced changes in turning parameters during smartphone use and the highest fall risk, such as individuals with Parkinson disease. Moreover, the experimental paradigm presented here might be useful in differentiating individuals with lower-back pain without and those with early or prodromal Parkinson disease. In individuals with subacute stroke, en bloc turning could represent a compensative strategy to overcome the newly occurring mobility deficit. Considering the ubiquitous smartphone use in daily life, this study should stimulate future studies in the area of fall risk and neurological and orthopedic diseases.
German Clinical Trials Register DRKS00022998; https://drks.de/search/en/trial/DRKS00022998
Turning-while-walking is relevant to everyday life and very common, accounting for >40% of steps taken in daily activities [
Previous evidence supports the negative association of an effective top-down sequence of body segments reorientation with the risk of falls, with people reorientating body segments more simultaneously being more prone to have multiple falls [
Turning is particularly dangerous when performed during multitasking. This term refers to the performance of multiple tasks simultaneously, such as walking and talking or driving while speaking at the phone. Multitasking is very common in everyday life, and several activities are performed while walking and turning. Performing a secondary task while walking (dual task [DT]) could negatively affect gait performance [
Similarly, no study to date has investigated the effect of smartphone use on turning behavior. This is a ubiquitous condition in everyday life, and in the last decade, some evidence has shown a detrimental effect of smartphone use on straight walking and balance [
To our best knowledge, this is the first study evaluating the effect of smartphone use on turning behavior in healthy participants of different ages and those with various neurological diseases.
Participants were recruited through flyers placed in public facilities (healthy participants) and in the Department of Neurology and outpatient clinics at University Hospital Schleswig-Holstein, Campus Kiel, Germany (neurological patients). Inclusion criteria were (1) being aged 18 years and older and (2) ability to walk independently without walking aids. Exclusion criteria were (1) a Montreal Cognitive Assessment (MoCA) score of <15 and (2) other movement impairments affecting mobility performance, as judged by the assessor. Participants were divided into 6 groups according to age and diagnosis. Healthy participants were divided into “young” (aged 18-60 years) and “older” (aged > 60 years). Participants with neurological disorders included individuals with Parkinson disease (according to the UK Brain Bank criteria [
The study was approved by the ethical committee of the Medical Faculty of Kiel University (D438/18) and was conducted in accordance with the principles of the Declaration of Helsinki. All participants provided written informed consent before the start of measurements. The study is registered in the German Clinical Trials Register (DRKS00022998, registration date: September 4, 2020).
Demographic data including age, sex, weight, and height were collected. Overall cognitive function at baseline was assessed with the MoCA [
Participants were asked to perform an overground walking and turning task on a 5-m-long walkway with a width of 1 m. Participants were asked to walk up and down the walkway at self-selected speed, thus including 180° turns to change walking direction (
Schematic representation of the 5-m walkway and the turning-while walking task.
A 12-camera 3D optical motion capture system (Qualisys AB) was used to record marker trajectories of passive retroreflective markers attached on the skin or tight clothing and footwear of the participants. Reflective markers were placed, among others, on the head, sternum, pelvis, and left and right feet. The exact placement of the markers is described elsewhere [
For the analysis of turning behavior, we calculated general turning parameters as well as segmental and intersegmental measures for the head, sternum, and pelvis. Regarding general parameters, turn duration, defined as the time in seconds between the beginning and ending of the turning phase, and the number of steps taken while turning were calculated. Concerning segmental turning measures, the peak angular velocity for each of the 3 body segments was measured. Finally, to investigate intersegmental coordination during turning in the temporal and spatial domains, we calculated intersegmental relative turning onset latencies and intersegmental maximum angles, respectively. These were calculated for each pair of segments for a total of 3 pairs. Turning onset latencies were determined using the more cranial one as a reference in each pair (sternum relative to the head, pelvis relative to the head, and pelvis relative to the sternum). A negative value indicates that the cranial segment started turning first. For each participant, variables were calculated as the average across turns for each of the 3 conditions.
To evaluate the impact of DT on turn duration, number of steps, and peak angular velocity for the 3 body segments, dual-task cost (DTC) was calculated for both SDT and CDT on the basis of equation 1 [
Statistical analyses were performed using JASP (version 0.16.1; JASP Team), R (version 4.0.3; The R Foundation), and RStudio (version 2022.02.2+433 for Windows; R Foundation for Statistical Computing). Descriptive statistics were calculated for the examined variables. To assess the difference in turn duration, number of steps, peak angular velocity, turning onset latencies, and maximum angles across the different groups and different conditions, mixed ANOVAs, corrected for gait speed, were used, with the factors “condition” and “group.” Post hoc
A total of 121 participants were enrolled in the study.
Demographics and clinical data of the enrolled groups.
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Young adults (N=36) | Older adults (N=18) | Participants with Parkinson disease (N=26) | Participants with subacute stroke (N=14) | Participants with multiple sclerosis (N=19) | Participants with lower-back pain (N=8) | |||||||
Age (years), mean (SD) | 28.9 (8.3) | 71.9 (6.3) | 63.3 (10.9) | 63.7 (16.6) | 38.5 (13.0) | 63.6 (16.8) | |||||||
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Male | 15 (42) | 9 (50) | 10 (38) | 3 (21) | 11 (58) | 3 (37) | ||||||
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Female | 21 (58) | 9 (50) | 16 (62) | 11 (79) | 8 (42) | 5 (63) | ||||||
Height (cm), mean (SD) | 180 (9) | 173 (10) | 175 (8) | 175 (11) | 179 (11) | 174 (10) | |||||||
Weight (kg), mean (SD) | 74.8 (14) | 78.4 (16.3) | 83.4 (15.2) | 81.4 (16.5) | 81.7 (21.2) | 79.8 (18.1) | |||||||
BMI, mean (SD) | 22.9 (3) | 26.1 (5.1) | 27.1 (4) | 26.4 (4.8) | 25.3 (4.7) | 26.3 (3.6) | |||||||
MoCAa score, median (IQR) | 29 (28-30) | 23.5 (21-27) | 25 (23-26) | 23 (20-26) | 28 (26-29) | 25 (24-27) | |||||||
SPPBb score, median (IQR) | 12 (12-12) | 11 (9-11) | 10 (8-11) | 11 (9-11) | 9 (7-11) | 12 (8-12) | |||||||
H&Yc score, median (IQR) | —d | — | 2 (1-3) | — | — | — | |||||||
MDS-UPDRS-IIIe score, median (IQR) | — | — | 22 (12-28) | — | — | — | |||||||
EDSSf score, median (IQR) | — | — | — | — | 1 (1-4) | — | |||||||
NIHSSg score, median (IQR) | — | — | — | 0 (0-3) | — | — | |||||||
pVASh score, median (IQR) | — | — | 3 (0-6) | — | — | 4 (1-6) | |||||||
FFbHi score, median (IQR) | — | — | 30 (27-32) | — | — | 3 (29-31) |
aMoCA: Montreal Cognitive Assessment.
bSPPB: Short Physical Performance Battery.
cH&Y: Hoehn and Yahr Scale.
dNot determined.
eMDS-UPDRS-III: Movement Disorder Society Unified Parkinson's Disease Rating Scale part III.
fEDSS: Expanded Disability Status Scale.
gNIHSS: National Institute of Health Stroke Scale.
hpVAS: visual analog scale of pain intensity.
iFFbH: Funktionsfragenbogen Hannover Scale.
Example of the turning detection algorithm output. Angular signals of the pelvis, sternum, and head are reported. The vertical lines indicate the start and end of a turn for each body segment.
Significant effects of factor “group” (
Significant effects of factor “group” and “condition,” but no significant interaction between the 2 factors were found for turn duration (
Significant effects of factor “group” and “condition” were found for peak angular velocity of the head (
Significant effects of factor “condition” were found for both turning onset latency of the sternum relative to the head (
Turning onset latencies by group (A) and task condition (B) of the sternum relative to the head. Mean of the variables is represented by bar height. SE of the mean is shown by the vertical lines. A negative value means that the cranial body segment starts turning first and vice versa. Significant pairwise comparisons are marked by horizontal lines and asterisks as follows: *
Turning onset latencies by group (A) and task condition (B) of the pelvis relative to the head. Mean of the variables is represented by bar height. SE of the mean is shown by the vertical lines. A negative value means that the cranial body segment starts turning first and vice-versa. Significant pairwise comparisons are marked by horizontal lines and asterisks as follows: *
Turning onset latencies by group (A) and task condition (B) of the pelvis relative to the sternum. Mean of the variables is represented by bar height. SE of the mean is shown by the vertical lines. A negative value means that the cranial body segment starts turning first and vice versa. Significant pairwise comparisons are marked by horizontal lines and asterisks as follows: *
Significant effects of factor “condition” were found for maximum angle between the head and sternum (
Maximum intersegmental angles by group (A) and task condition (B) between sternum and head. Mean of the variables is represented by bar height. SE of the mean is shown by the vertical lines. Significant pairwise comparisons are marked by horizontal lines and asterisks as follows: *
Maximum intersegmental angles by group (A) and task condition (B) between pelvis and head. Mean of the variables is represented by bar height. SE of the mean is shown by the vertical lines. Significant pairwise comparisons are marked by horizontal lines and asterisks as follows: *
Maximum intersegmental angles by group (A) and task condition (B) between pelvis and sternum. The mean of the variables is represented by bar height. SE of the mean is shown by the vertical lines. Significant pairwise comparisons are marked by horizontal lines and asterisks as follows: *
A significant effect of factor “DT condition” (
More details regarding the pairwise comparisons for the investigated variables can be found in the
Dual task cost of peak angular velocity of the head by group (A) and task condition (B). The mean of the variables is represented by bar height. SE of the mean is shown by the vertical lines. Significant pairwise comparisons are marked by horizontal lines and asterisks as follows: *
This cross-sectional study aimed at evaluating the effects of concurrent active smartphone usage and turning-while-walking on the dynamics of intersegmental coordination of turning. Both turning and smartphone use during walking are common in human life, and reduced turning coordination could lead to an increased risk of falling [
We found that all participants, irrespective of age and neurologic disease, showed an en bloc turning behavior when using a smartphone; participants with Parkinson disease showed the most pronounced reduction in peak angular velocity, with a significant difference for the DTC of head segment compared to lower-back pain; and that our participants with subacute stroke turned en bloc even without a smartphone. These results are discussed in detail in the following paragraphs.
All groups turned en bloc while performing a cognitive task on a smartphone irrespective of age and neurologic condition. Although the direct effect of smartphone use on tuning has not been explored to date, reports investigating the influence of smartphone on straight walking and balance showed a reduction in gait speed [
We found that participants with Parkinson disease showed the lowest head peak angular velocity in all conditions. They also showed the longest turn duration and needed most steps for the turns. This was an expected result considering that bradykinesia and rigidity as well as reduced gait speed and increased cadence with shorter step length are typical features of Parkinson disease [
Participants with lower-back pain were the only group that did not show any significant difference in head peak angular velocity when using a smartphone, compared with ST. This was particularly interesting due to the following observation. Although participants with Parkinson disease and those with lower-back pain were comparable concerning demographic and clinical (including pain intensity) parameters, both groups were remarkably different when comparing head peak angular velocity DTC (AUC of 0.96 and 0.92 for SDT and CDT, respectively, see also
In our participants with subacute stroke, despite the head started turning slightly before sternum and pelvis, there was no significant difference in turning onset latencies among the 3 segment pairs even in the turning-while-walking–only condition. We hypothesize that en bloc turning may not be deleterious under all circumstances but, for example, in acute or subacute medical situations, may even serve as a compensative strategy to overcome the newly occurring mobility deficit. Increased cocontraction and impedance control with the goal of reducing kinematic errors, stabilizing movement, and increasing performance is a common strategy used in the early phases of motor learning when new dynamics have to be acquired [
This study faces some limitations. First, the sample size at least of some groups, the range of disease severity, and the generally relatively high level of physical and cognitive abilities of our participants may limit the generalizability of our results, and further studies including participants with lower functional scores, greater disease severity, and more severe cognitive impairment may be helpful to address this. Second, in this proof-of-concept study, we chose a 180° turn paradigm. However, we are aware that other, primarily smaller turns are also performed in everyday life, and future studies should investigate the influence of smartphone use on these turns. Third, on average, the turning algorithm used in this study underestimated the turning magnitudes by 10%-15%. This could likely be attributed to the general structure of the algorithm (see the
Performing a secondary task on a smartphone leads to a more en bloc turning irrespective of age and neurologic condition. The segmental turning behavior of participants with Parkinson disease suggests that this disease could be most affected by smartphone use and these participants could be at high risk of falling when turning while using a smartphone. Considering the ubiquitous smartphone use in daily life, results of this study could stimulate future studies in this area, as well as, in clinical routine, the type of history taken from elderly and neurologically ill individuals who have increased risk of falling during ambulation.
Supplementary figures and tables.
complex dual task
dual task
dual-task cost
Montreal Cognitive Assessment
simple dual task
single task
The authors sincerely thank all people that were involved in the data collection, from study participants to students who aided and assisted with the assessments. For this publication, we acknowledge financial support by DFG within the funding program Open Access Publikationskosten.
Data of a subgroup of healthy participants included in our study are published digitally [
EW, CH, and WM designed the study. RB and KS helped with participant recruitment and data collection. EW collected data. EW and EB performed data analyses. EB and WM wrote the first draft of the manuscript. EW, RR, SH, RB, KS, FEP, and CH reviewed the manuscript draft. All authors contributed to the article and approved the submitted version.
None declared.