A Personalized Sensor Support Tool for the Training of Mindful Walking [original]

A Personalized Sensor Support Tool

for the Training of Mindful Walking*

R¨

udiger Pryss1, Manfred Reichert1, Dennis John2, Julian Frank1, Winfried Schlee3and Thomas Probst4

Abstract— The exploitation of sensor features offered by

present smart mobile devices is a trend that becomes increas-

ingly important in various domains. In healthcare, for example,

these sensors are used to cheaply gather valuable data for

chronic disease management or health care. Regarding the

latter, health insurers crave for effective methods that can be

offered to their customers. Moreover, smart mobile devices

provide many advantages compared to approaches hitherto

applied in the aforementioned contexts as they can be easily

used in everyday life. Thereby, when taking these advantages

properly into account, new mobile application types become

possible. Body sensor networks are such an application type that

aim at monitoring users in vivo. Furthermore, data gathered

with body sensor networks may be a valuable basis to provide

user interventions. This paper presents an application that shall

support users to walk mindfully. The motivation was to create

a mobile tool that can make mindful walking more effective

to reduce stress and to target noncommunicable diseases such

as diabetes or depression. It is a mobile personalized tool that

senses the walking speed and provides haptic feedback thereof.

The mindful walking procedure, the technical prototype as well

as preliminary study results are presented and discussed in

this work. The reported user feedback and the study results

indicate promising perspectives for a tool that supports a

mindful walking behavior. Altogether, the use of smart mobile

device sensors constitutes a promising instrument for realizing

mobile applications in the context of health care and disease

management.

Index Terms— mHealth, body sensor network, mindful walk-

ing, digital health care

I. INTRODUCTION

Mindfulness has been defined as the intentional and non-

judgmental attention to experiences of the present moment

[1]. Mindfulness is rooted in eastern meditation traditions

and has become highly relevant in basic research [2] as well

as in health [3] and clinical science [4]. Many mindful-

ness exercises applied, for example, in Mindfulness-based

Stress Reduction (MBSR) [1] or Mindfulness-based Cog-

nitive Therapy (MBCT) [5] instruct participants to inten-

tionally and non-judgmentally attend to automated body-

related processes (e.g., breathing, walking). One of these

body-related mindfulness exercises is walking mindfully [6].

The participants are instructed to become conscious of the

otherwise automated walking process by walking slowly,

*This work was not supported by any organization

1Faculty of Computer Science, Engineering and Psychology, Ulm Uni-

versity, Germany

{ruediger.pryss,manfred.reichert,julian.frank}@uni-ulm.de

2FOM University of Applied Sciences, Germany [email protected]

3University Hospital Regensburg, Germany

[email protected]

4Donau Univ. Krems, Austria [email protected]

taking small steps and by fully focusing on walking. Mindful

walking has, for example, been shown to be beneficial for

patients with depression [7] as well as for patients with

diabetes [8]. During mindful exercises, however, participants

often experience that their mind is distracted from being

mindful and that they have difficulties to redirect their focus

on the mindful exercise, especially patients suffering from

depression [9]. Moreover, novices are often insecure how to

practice mindfulness. Mobile applications may help users to

practice mindfulness as well as to stay mindful and to refocus

the attention during mindful exercises. In this paper, a mobile

application is presented that supports users to walk mindfully

by sensing the individual walking speed and by providing

continuous haptic feedback on the individual walking speed

during the mindful walking exercise. In general, feedback has

been shown to improve performance in various domains [10].

In the context of mindfulness, text message feedback [11] as

well as feedback on EEG data to deepen mindfulness was

evaluated previously [12]. To support a mindful walking, [13]

performed a study and compared visual, auditory, and visual-

auditory feedback on the walking. In the current work, the

realized prototype consists of mobile applications developed

for the Apple iPhone and for the Apple iWatch. The two

applications are tightly coupled via Bluetooth and represent

the basis for the mindful walking. On the iWatch, a haptic

feedback feature was implemented. As other works show

[14], [15], such a feature may increase the user experience

properly. When concerning the two main goals pursued by

body sensor networks, the realized prototype contributes with

this features as follows:

(1) Enable the user to measure his or her usual walking speed in

vivo. The measurement, in turn, is enhanced by a familiarization

phase. (2) Provide haptic feedback (i.e., an intervention) to the user

if his or her walking speed level exceeds the mindful one, which

will be defined by the user during the familiarization phase.

The main motivation behind this work was to develop a

mobile application to support individuals in mindful walking

- especially those practicing mindfulness is challenging for

like novices or patients with depression [9] - with the final

aim to increase its benefits for example for stress reduction

and the management of noncommunicable diseases [7], [8].

The way how the technical prototype was realized and how

the first study with this prototype was conducted will be

presented in this paper. Our pilot study investigates the

hypotheses whether the usual walking speed is faster than the

walking speed during the mindful walking exercise as well

as whether the walking speed during the mindful walking

exercise is not statistically different from the target walking

speed the participants set for the mindful walking exercise.

The obtained results of the pilot study support the hypotheses

and indicate that a mobile application for a mindful walking

may constitute a proper health care support tool in everyday

life. The remainder of this paper is organized as follows.

In Section II, the used procedure for the mindful walking is

presented, while Section III discusses the technical prototype.

Section IV, in turn, discusses study results and Section V the

related work, which is relevant in the context of this paper.

Finally, Section VI concludes the paper with a summary and

an outlook.

II. MINDFUL WALKING PROCEDURE

To support users in exercising mindful walking via the

application, the procedure shown in Fig. 1 must be accom-

plished.

iPhone iWatch

Start

User Input:

SAM

Questionnaire

Normal Speed

Instructions

Info Screen Start

Measurement

results

User Input:

Target Speed

& Duration

Monitoring Screen

Input Screen

Mindful

Walking

Instructions

Info Screen Start

{target speed, duration}

Measurement

Check for

Violation

Check for

Duration

Feedback

results

User Input:

SAM

walking period

reached

Questionnaire

store

data

General Information 1

store

data 4

Fig. 1: Mindful Walking Procedure

More specifically, the procedure comprises the following

steps in the presented order:

First, a general information on the mindful walking will

be displayed on the iPhone application (cf. Fig. 1, 1

).

Second, the user rates his or her current valence, arousal,

and dominance by the so-called Self-Assessment Manikin

(SAM) [16] (cf. Fig. 1, 2

).

Third, the usual walking speed of an user will be deter-

mined. For this, the user will be instructed by the iPhone

application to walk in his or her usual speed for 5 minutes:

“Now walk normally for 5 minutes for the measurement of

your current walking speed. You will hear a sound as soon

as the measurement is complete” (cf. Fig. 1, 3

). Then, the

user switches to the iWatch application for the 5 minutes

measurement.

Fourth, after the 5 minutes, the user receives a feedback

on his or her walking speed on the iWatch application (e.g.,

“Your walking speed is 3.73 km/h”; (cf. Fig. 1, 4

)). Then

he or she can choose from the following four pre-defined

options to set the “target” walking speed for each body

walking exercise (e.g., walking speed is 4.0km/h and users

selects 75% reduction (i.e., “target” speed = 1.0km/h))1:

•10% reduction of the walking speed.

•25% reduction of the walking speed.

•50% reduction of the walking speed.

•75% reduction of the walking speed.

Fifth, again after the 5 minutes, the assessed data (user id,

date, time, SAM, walking speed) are transferred to a database

(cf. Fig. 1, 4

).

Sixth, in the next step, the participant receives a general

instruction on mindful walking (cf. Fig. 1, 5

). “You are to

begin a mindful walking exercise: When walking mindfully,

please try to notice at least these four basic components of

your steps”:

•The lifting of one foot.

•The moving of the foot a bit forward of where you are standing.

•The placing of the foot on the floor, heel first.

•The shifting of the weight of the body onto the forward leg as the

back heel lifts, while the toes of that foot remain touching the floor

or the ground.

At the end of this step, the user gets the information: “You

will get haptic feedback (i.e., a vibration) each time your

speed level is higher than the speed level you set as the goal

for this exercise. In case you feel the vibration, please try to

walk slower. You can stop the exercise at any time, but you

should try to walk mindfully for at least 15 minutes. You

will hear a sound after each 5 minutes are passed, but you

can continue the exercise as long as you want”.

Seventh, the mindful walking exercise must be accom-

plished, feedback on the exercise is provided and question-

naires (e.g., SAM) are administered after each exercise (cf.

Fig. 1, 6

&7

).

The prototype also includes a feature that enables users to

set an individual schedule at which days and times in daily

life they want to receive a notification by the application as

a reminder to train mindful walking. However, the use of the

application is also possible whenever they want to practice

mindful walking regardless of the notifications.

III. TECHNICAL PROTOTYPE

A mobile application was implemented for the Apple

iPhone (iOS 11 beta), including the option to run the applica-

tion also on the Apple iPad. In addition, a mobile application

for the Apple iWatch (watchOS 3.2.3) was implemented. The

two applications are coupled via Bluetooth. Note that both

on the iPhone and the iWatch, a user gets an alert if the

coupling was not accomplished. Data, which is produced on

the iWatch, is locally stored there and then transferred to the

iPhone.2Only after a successful transfer is accomplished,

1A future version of the application will also include an open entry for the

user to set his individual target walking speed for each exercise (prerequisite:

target walking speed<usual walking speed).

2Note that we are also working on an iWatch version that directly transfers

data from the iWatch to a remote database.

the data is erased on the iWatch. All data on the iPhone, in

turn, is transferred to a relational database via REST calls. In

the following, selected impressions of the two applications

are presented. In Fig. 2, two iPhone screens corresponding

to the phases 5

&7

(cf. Fig. 1) are shown. Fig. 3, in turn,

illustrates two iWatch screens that correspond to the phases

&6

(cf. Fig. 1) of the mindful walking procedure.

Fig. 2: iPhone Screens: Training Details

Fig. 3: iWatch Screens: Measurement & Monitoring

IV. PILOT STUDY RESULTS

In a pilot study, the mindful walking applications were

tested in N= 20 participants. The participants used the

mindful walking applications once; n= 19 participants

set 15min as training interval and n= 1 participant set

10min. The participants usual walking speed as measured

by the iWatch application was on average M= 3.37 km/h

(SD = 0.35). The average target walking speed the par-

ticipants set for the mindful walking exercise was M=

3.16 km/h (SD = 0.33), and the average walking speed

during the mindful walking exercise as measured with the

iWatch application was M= 3.13 km/h (SD = 0.28).

A repeated measurement analysis of variance (rANOVA)

was conducted in SPSS 24 to test whether the usual

walking speed, the target walking speed, and the walking

speed during the mindful walking exercise are significantly

different. The rANOVA (Greenhouse-Geisser corrected) pro-

duced a statistically significant result indicating relevant

differences between the three walking speeds (usual walking

speed, target walking speed, and walking speed during the

mindfulness exercise): F(1.09; 20.67) = 29.13; p < 0.01.

Moreover, simple contrasts (with the walking speed during

the mindful walking exercise as reference) were performed

within the rANOVA to evaluate the hypotheses whether

the usual walking speed is faster than the walking speed

during the mindful walking exercise as well as whether

the walking speed during the mindful walking exercise is

not statistically different from the target walking speed the

participants set for the mindful walking exercise. The results

were in correspondence with the hypotheses: The walking

speed during the mindful walking exercise was significantly

slower than the usual walking speed (F(1; 19) = 30.48; p <

0.01) and the walking speed during the mindful walking

exercise was not significantly different from the walking

speed the users set as target for the mindful walking exercise

(F(1; 19) = 0.36; p= 0.55). Finally, we used a paper-based

questionnaire to evaluate the overall user experience of the

mobile applications. Thereby, the users mainly reported very

positive feedback.

V. RELATED WORK

In general, other emerging paradigms exploiting smart

mobile device capabilities have already shown that daily

life behavior can be properly captured in the context of

health care [15], [17]. Concerning the use of smart mobile

devices in the context of mindfulness, recent related works

have been presented [18], [19]. Despite the advantages of

smart mobile devices, their drawbacks must also be carefully

considered [20], [21]. Mobile applications that directly cope

with a mindful walking have also been introduced. In [22],

for example, the authors propose a mobile application using

the individual walking speed (accelerometer) as well as the

individual breath (microphone) to provide real-time ambient

sound at certain frequencies to the user. [13], in turn,

described a system for smartphones, which assesses walking

in real time and provides immediate visual-auditory feedback

to support a mindful walking. However, contrary to our study,

no haptic feedback, but visual-auditory feedback was applied

and users needed a pair of sensing shoes (to provide feedback

on the walking pattern as well). Yet, wearing sensing shoes,

looking at the smartphone screen for visual feedback, or

hearing auditory feedback (silent surrounding or headphones

required) might not always be possible in daily life. Other

mobile applications intended to generally foster mindful-

ness have also been studied, e.g., [23], [24]. In general,

the exploitation of smart mobile device sensor features for

disease and health care management becomes increasingly

important. In the context of tinnitus, for example, sensors

in combination with serious games are used to measure the

hearing ability of patients [25]. However, such methods have

been less considered in the context of a mindful walking.

Altogether, neither existing approaches propose a mobile

application like presented here for a mindful walking nor

do they present the technical procedure in more detail.

VI. SUMMARY AND OUTLOOK

This paper presented an application that was developed

to support individuals in walking mindfully. The application

integrates sensors to measure the walking speed in daily life

situations and during mindful walking exercises. Moreover,

a feature was implemented to provide immediate haptic

feedback on the sensed walking speed. The feedback feature,

in turn, was realized as it might prevent individuals from

walking faster than intended and from “mind wandering”

during the mindfulness exercise. Note that haptic feedback

might be more suited in daily life than visual or auditory

feedback as it is not always possible to look at the mobile

device screen to see visual feedback or to be in silent

surroundings / to wear headphones to hear auditory feedback.

A pilot study was performed, which revealed promising

results. The data of the walking speed sensor showed that the

participants’ usual walking speed is faster than the walking

speed during the mindful walking exercise. In line with this

result, [13] reported that their system to support mindful

walking also slowed down the walking speed. Moreover, the

sensed walking speed during the mindful walking exercise

was not different from the walking speed the participants

set as target speed for the mindful exercise. The result that

the participants could achieve their intended “slow speed”

might suggest that the haptic feedback feature can be applied

successfully. Yet, more evaluations are necessary and future

experiments should include a control condition. Without the

haptic feedback feature so that more causal conclusions

might be possible on whether the haptic feedback feature

is indeed helpful to walk mindfully as slowly as intended

and to stay mindfully during the exercise. It could also be

possible that the feedback distracts the participants from

being mindful. Moreover, feedback of any kind could create

a judgmental stance towards the walking, which is against

the mindfulness principles. We plan further studies using

psychometric questionnaires (e.g., Five Facet Mindfulness

Questionnaire) to explore how the feedback feature affects

different aspects of mindfulness (e.g., nonjudging of inner

experience or nonreactivity to inner experience). Note that

only a small sample was investigated and, hence, the gener-

alizability of the results is limited. Larger trials are planned

to investigate not only the impact on different facets of

mindfulness, but also whether the SAM ratings given before

the exercise have an impact on the mindful exercise, and

whether the SAM ratings, state body mindfulness [26] and

well-being [27] change due to exercising mindful walking

with the application. Studies to compare a condition using the

mindful walking application, a condition exercising mindful

walking traditionally (e.g., guided by an expert, instructions

delivered by audio, or video), and a waiting list control

condition will be performed. Additionally, further studies are

planned in occupational settings (e.g., occupational health

management). Finally, we currently evaluate the measured

walking speed on more sensors like the Garmin 920XT. In

summary, the newly developed mindful walking application

has been successfully applied to sense the walking speed

and to provide immediate feedback on the current walking

speed. The presented pilot study results are promising and

the mindful walking application offers several opportunities

for digital health care.

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