Ski Tip Display: Design and Implementation of an Unobtrusive Ski

Mounted Visual Feedback System for Alpine Skiing

Thomas Grah

1,2 a

Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria

Department of Artiﬁcial Intelligence and Human Interfaces, Paris-Lodron University Salzburg, Salzburg, Austria

Keywords:

Skiing, Visual Feedback, Terminal Feedback, Field Study.

Abstract:

This paper presents the design, implementation, and ﬁeld evaluation of SkiTip Display, a ski-mounted LED

feedback system that provides terminal visual feedback on carving angle to support skill development in alpine

skiing. Developed through a participatory design process with domain experts, the system was deployed

in-the-wild and tested with nine recreational skiers. Results from sensor-based metrics and post-session in-

terviews suggest that ski-mounted visual feedback is perceivable, motivating, and well-suited for post-run

reﬂection, though not actionable during motion. We report key lessons on feedback timing, simplicity, and

trust, and discuss implications for designing embedded performance feedback in high-speed outdoor sports.

This work contributes to the ﬁeld by expanding the design space for equipment-integrated feedback systems

and by articulating challenges of in-the-wild deployment in dynamic environments.

1 INTRODUCTION

In alpine skiing, developing technique requires con-

tinuous feedback — often available only through in-

person instruction or self-assessment based on de-

layed, indirect information. While commercial sys-

tems such as ski-tracking smartphone apps or wrist-

worn devices offer post-run summaries, these tech-

nologies typically provide numerical feedback, rely

on limited screen interfaces, and are hard to use in

cold, fast-paced environments, especially when wear-

ing gloves (Mencarini et al., 2019b; Colley et al.,

2018). The need remains for a lightweight embedded

device that can provide timely feedback and integrate

directly into the ﬂow of skiing without disrupting it.

We address this gap through the SkiTip Display,

a ski-mounted LED feedback system designed to

present terminal feedback (Walsh et al., 2009) —

feedback provided immediately after performance -

directly on the equipment. By leveraging the ski as a

feedback surface, we explore the unique affordances

of peripheral visibility and embodied integration in

a context where traditional display surfaces are often

inaccessible or unsafe to consult during motion. Prior

work has investigated feedback displays on boards in

other snow sports, such as snowboarding (Park and

https://orcid.org/0000-0002-4588-1249

Lee, 2016b; Park and Lee, 2016a), and on shoes

for running and cross-country skiing (Colley et al.,

2018), but it remains unclear how such approaches

translate to alpine skiing with its speciﬁc postures,

edge control demands, and speed constraints.

We focus speciﬁcally on carving angle, the in-

clination of the ski relative to the snow surface dur-

ing a turn, as a domain-relevant performance indica-

tor. Carving angle is closely associated with advanced

ski technique and is widely used in instruction and

coaching to evaluate edge control, turn quality, and

skier progression (Sigrist et al., 2013). It is also read-

ily measurable via inertial sensing, and is intuitive

enough to be communicated through simple visual ab-

stractions on the ski itself.

This paper explores the feasibility and value of

ski-mounted visual feedback systems through the de-

sign, implementation, and ﬁeld deployment of Ski-

Tip Display. The system was developed in collabora-

tion with expert skiers via participatory design work-

shops and evaluated in-the-wild with nine recreational

skiers.

We address the following research questions:

• RQ1: How can skis be used as a display medium

for terminal feedback in alpine skiing?

• RQ2: What are skiers’ perceptions of ski-

mounted feedback after repeated use in realistic

Grah, T.

Ski Tip Display: Design and Implementation of an Unobtrusive Ski Mounted Visual Feedback System for Alpine Skiing.

DOI: 10.5220/0013717200003988

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 13th International Conference on Sport Sciences Research and Technology Support (icSPORTS 2025), pages 191-199

ISBN: 978-989-758-771-9; ISSN: 2184-3201

191

Figure 1: The SkiTip Display system on snow during the user study.

slope conditions?

• RQ3: How do carving angle metrics evolve with

exposure to such feedback, and what contextual

factors (e.g., fatigue, snow conditions) inﬂuence

this?

Through this work, our objective is to contribute a

situated understanding of equipment-integrated feed-

back in alpine sports and to reﬂect on the design chal-

lenges and opportunities of deploying such systems in

real-world outdoor environments.

2 RELATED WORK

We situate our work within the domains of

technology-enhanced alpine sports and the broader

landscape of feedback systems in sports, particularly

in relation to feedback modality, timing, and embodi-

ment.

2.1 Feedback Systems in Alpine Snow

Sports

Digital tools for skiing and snowboarding increas-

ingly support skill acquisition through motion track-

ing, performance visualization, and gamiﬁed feed-

back. Prior systems have mounted feedback displays

on snowboards (Park and Lee, 2016b) or integrated

feedback into boot or helmet accessories. However,

these systems typically offer coarse-grained informa-

tion or use displays that are not in the skier’s periph-

eral view. Our approach is most directly inspired by

snowboard-mounted displays (Park and Lee, 2016b),

but differs in several key respects: skiing posture lim-

its opportunities for direct visual attention to the skis

during movement, and carving technique places more

emphasis on sustained edge angles and turn shape.

Our system focuses on post-run feedback (terminal),

allowing skiers to reﬂect on performance without

compromising on-slope safety.

2.2 Wearable and Embedded Feedback

Systems

More broadly, researchers have explored wearable

and embedded systems that support bodily awareness

and training. Colley et al. (Colley et al., 2018) pro-

posed shoe-mounted displays for running, and differ-

ent feedback modalities have been applied to a variety

of sports (e.g., running (Jensen and Mueller, 2014;

Mueller and Muirhead, 2015; Van Rheden et al.,

2024), swimming (Wiesener et al., 2019; B

achlin

et al., 2009), climbing (Mencarini et al., 2019a), and

dancing (El Raheb et al., 2018; El Raheb et al.,

2019)). Feedback modality has been a central con-

cern, with comparative studies of visual, auditory, and

haptic feedback showing trade-offs in terms of at-

tention, bodily integration, and timing (Sigrist et al.,

2013). Unlike wrist-worn or audio systems, our ski-

mounted display aims to provide immediate, spa-

tially grounded feedback using a surface already in

the skier’s visual ﬁeld when stationary. This explores

an under-addressed modality-location pairing: visual

feedback on equipment rather than on-body or audi-

tory overlays.

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192

2.3 Timing and Modality of Feedback

The timing of feedback signiﬁcantly shapes its ef-

fectiveness in motor learning. Sigrist et al. (Sigrist

et al., 2013) distinguish between concurrent feedback

(during action) and terminal feedback (after comple-

tion). While concurrent feedback may disrupt perfor-

mance in dynamic, high-risk sports like skiing, termi-

nal feedback offers a safer alternative, enabling reﬂec-

tion without cognitive overload or safety trade-offs.

Our design prioritizes terminal feedback, communi-

cated through a color-coded LED visualization im-

mediately after a run. This allows skiers to connect

the visualization to their just-completed performance

while stationary, without interfering with run-time at-

tention.

2.4 Summary

In contrast to prior work on wearable devices and

snow sport augmentations, our system uniquely ex-

plores ski-mounted terminal feedback for carving an-

gle awareness. We contribute an empirical evaluation

of this design in ﬁeld conditions, and reﬂect on the

user experience of embedded feedback directly inte-

grated into sports equipment.

3 APPROACH AND

METHODOLOGY

3.1 Approach and Methodology

The development of the SkiTip Display followed a

multi-stage process involving expert consultation, it-

erative prototyping, and in-situ evaluation. The over-

all objective was to design and assess a ski-mounted

feedback system capable of supporting skill develop-

ment through terminal visual feedback.

3.2 Expert Workshop

To inform the initial design, a structured participatory

workshop was conducted with six domain experts, in-

cluding two certiﬁed ski instructors, two competitive

skiers, and two HCI researchers specializing in sports

technology. The workshop, lasting approximately 2.5

hours, was organized into three phases. First, a con-

textual inquiry was carried out, during which partic-

ipants were asked to reﬂect on common challenges

encountered during technique development in alpine

skiing, as well as their experiences with existing feed-

back systems such as smartphone applications and

wearable devices. Second, an ideation session was

facilitated. Participants, working in two groups, were

prompted to generate concepts for embedded feed-

back systems. Each group was provided with work-

sheets and sketching materials and was asked to con-

sider locations for feedback display, suitable infor-

mation modalities, and preferred timing of feedback.

Third, a consolidation and reﬂection phase was con-

ducted. Each group presented its concepts, which

were then evaluated through guided discussion based

on visibility, intuitiveness, safety, and feasibility in

outdoor skiing conditions. In total, 55 distinct de-

sign ideas were generated. These were subsequently

analyzed using open coding and afﬁnity mapping to

identify cross-cutting themes. It was found that pe-

ripheral visual feedback was generally preferred, and

that feedback was considered most useful when pre-

sented immediately after a skiing run. The ski it-

self—particularly the tip region—was identiﬁed as

a promising location for integrating such feedback.

These ﬁndings informed the subsequent design phase.

3.3 Design Rationale

The tip of the ski was selected as the display loca-

tion based on its visibility while stationary, minimal

interference with skiing movement, and potential for

integration into existing equipment. This approach

aligns with broader trends in embodied sports tech-

nologies that emphasize minimal intrusiveness and

environmental robustness (Mencarini et al., 2019b).

Carving angle was chosen as the primary performance

metric. This parameter, deﬁned as the inclination of

the ski relative to the snow surface during turning, is

frequently used by instructors as an indicator of edge

control and technical proﬁciency. Furthermore, the

carving angle can be reliably estimated using iner-

tial measurement data, and its range can be intuitively

encoded through color-based visualizations. It has

been identiﬁed as a central quality metric for carved

skiing turns by M

uller and Schwameder (M

uller and

Schwameder, 2003).

3.4 Visual Design

The visual design was developed to represent the

mean carving angles reached during one run in the

most simpliﬁed way (See ﬁgure 2). The green bar (a)

represents the mean carving angle of the last run. The

purple line (b) indicates the respective previous run.

Point (c) references the individual maximum carving

angle, which was derived from the baseline runs max-

imum + 10° rotation angle.

Ski Tip Display: Design and Implementation of an Unobtrusive Ski Mounted Visual Feedback System for Alpine Skiing

193

Figure 2: The visual design of the feedback on carving an-

gles with ski-mounted displays in alpine skiing.

3.5 Prototype Implementation

The prototype system consisted of the following com-

ponents (See ﬁgure 3):

a) A pair of Bluetooth-connected, six-axis Inertial

Measurement Units (IMUs; Atomic Movesense)

strapped to the shafts of standard ski boots.

b) An Android smartphone (Samsung Galaxy A52S

5G) running an application that collects and pro-

cesses the IMU data, then triggers visualization.

c) An ESP-32 microcontroller (ESP32-Wroom)

serving as a Wi-Fi access point for the smartphone

and as the data hub for the ESP-NOW network.

d) A pair of skis equipped with the SkiTip Display

ESP32 PICO-D4 microcontrollers on a custom

light-emitting diode (LED) controller printed cir-

cuit board (PCB). These receive the processed

data and handle the visualization. Each microcon-

troller is wired to an LED display and mounted on

a ski in a waterproof housing with its own battery.

Upon completion of a skiing run and subsequent

deceleration to a stationary state, the system com-

puted the mean carving angle over the run and dis-

played the result via the ski-mounted LEDs. The

feedback was presented for a brief interval before be-

ing reset. Multiple iterations were performed to im-

prove system visibility under varying lighting condi-

tions, robustness in snow environments, and synchro-

nization between motion states and feedback presen-

tation.

3.6 Smartphone-Based Skiing Quality

Assessment

An Android smartphone (Samsung Galaxy A52S 5G)

was used to a) connect to and receive data from two

shaft-mounted IMUs, b) collect GPS data (location,

speed, and elevation), and c) implement an activ-

ity recognition chain as presented by Jølstad et al.

(Jølstad et al., 2021) using the methods described by

Martinez et al. (Mart

ınez et al., 2019) to calculate

skiing turns in near real-time (with a maximum de-

lay of about 10s). In the next step, c) classiﬁcation

features (based on speed, turn radius, edge angle, and

g-force) are calculated that are ﬁnally used to d) clas-

sify those turns [Neuwirth, 2020] into carved and non-

carved turns, assigning a quality score to carved turns

(1-10, with scores greater than two indicating parallel

turns, and scores seven to ten indicating carved turns).

Carved turns are then further analyzed, each turn split

into three phases (“initiation”, “turning” and “com-

pletion“ phase), with the edge angle calculated during

the “turning” phase where the angle is largest. Edge

angle for a run was calculated for each ski (left and

right), using the mean value of the outer skis, since

the greatest load during the turning phase is on this

ski for classic parallel turns, and still high for carved

turns (M

uller and Schwameder, 2003). This informa-

tion was e) then presented to the user after each run,

once a stop was detected based on GPS data, on the

app, and on the SkiTip Display.

3.6.1 Detection of Each Run

The boot-mounted IMUs’ 3-axis rotation and 3-axis

acceleration data is constantly recorded by the An-

droid smartphone each participant carries. The start

and end of the run are detected based on the algo-

rithm presented by Jølstad et al. (Jølstad et al., 2021).

To isolate active skiing runs from periods spent on

the lift or waiting, an algorithm was applied that

identiﬁes the beginning of a run whenever the An-

droid phone’s GNSS-derived altitude was decreasing

and the GNSS-derived speed from an Android smart-

phone exceeded 2 m/s. A run is considered ﬁnished

once the speed dropped below 1 m/s.

3.6.2 Computation of the Edge Angle

Edge Angle calculation is a two-step process. First,

the run is segmented into distinct turns based on the

algorithm presented by Mart

ınez et al. (Mart

ınez

et al., 2019). To derive the edge angle, the y-axis (roll

angle) of the gyroscope signal for both skis is ﬁltered

and integrated over the time of a turn, representing the

edge angle. To account for a possible drift of the gy-

roscope signal, the result is further normalized based

on the assumption that each turn starts and ends at an

edge angle of 0°. The maximum edge angle of each

turn of the run is then extracted for the outer ski for

right turns and left turns. Finally, the overall mean

of all maximum edge angles is calculated. The ﬁrst

and the last turns are ignored because those are usu-

ally half-turns. The mean of the remaining outer ski

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194

Figure 3: The components of the SkiTip Display prototypes, including the wireless connections: (a) pair of ski-boot mounted

ATOMIC movesense IMUs; (b) Android smartphone with a custom app; (c) ESP-NOW to WiFi Hub; (d) pair of SkiTip

Displays.

edge angles is ﬁnally presented on the respective ski

(left ski: outer ski for right turns, right ski: outer ski

for left turns).

3.7 Hardware

The SkiTip Display was designed as a standalone, wa-

terproof system with an integrated battery. It con-

tains an ESP32 PICO-D4 module (Unexpected Maker

TinyPICO NANO) on a custom PCB, ensuring a

lightweight, compact system that drives an 8 × 32 red-

green-blue (RGB) LED matrix.

3.8 Custom LED Controller Board

The custom PCB (Figure 4) was designed to ﬁt within

a waterproof enclosure, leaving space for a LiPo bat-

tery. It integrates: (a) an Unexpected Maker TinyPico

Nano ESP-32 PICO-D4 board, (e) three logic-level

converters (3.3 V to 5 V) for segmented LED dis-

plays, (c) a connector for a 2S (7.4 V) LiPo battery

with under-voltage protection, (b) a pin header for

USB programming, (f) a backside connector for the

LED matrix, a reset button and a RGB status LED,

and an external for the voltage converter (d).

3.9 LED Matrix

Each ski-mounted display consists of 256 WS2182B

RGB LEDs on a ﬂexible PCB. To waterproof the ma-

trix, both sides were sprayed with two layers of Plas-

tik 70 and afﬁxed to the ski using double-sided tape.

The edges were reinforced with black liquid rubber

paint to prevent water ingress, and ﬁve layers of trans-

parent liquid rubber spray provided additional protec-

tion against moisture and mechanical stress (e.g., con-

tact between skis).

Figure 4: A photo of the custom LED controller PCB and

the step-down-converter.

4 FIELD STUDY

To evaluate the feasibility and user perception of the

SkiTip Display, a ﬁeld study was conducted under

real-world skiing conditions. The study aimed to ex-

plore skiers’ experiences with ski-mounted terminal

feedback and to gather preliminary data on changes

in carving angle performance across repeated runs.

4.1 Participants and Setting

Nine recreational skiers (5 male, 4 female, aged

22–47) were recruited via convenience sampling. All

participants self-reported intermediate to advanced

skiing ability and were familiar with the use of wear-

able sports technology. Written informed consent was

obtained from all participants prior to data collec-

tion. The study was conducted on a marked, easy

(difﬁculty rating: blue), about 500m long slope with

120m difference in height (m= 24%/13.5° slope) at

a European ski resort over ﬁve consecutive days.

Weather conditions were generally stable, with occa-

Ski Tip Display: Design and Implementation of an Unobtrusive Ski Mounted Visual Feedback System for Alpine Skiing

195

sional variation in visibility and snow quality. Par-

ticipants were instructed to use a standardized set of

skis onto which the SkiTip Display system had been

mounted. Wearing a helmet was mandatory, and stan-

dard safety precautions were followed throughout.

4.2 Study Procedure

Each participant completed a total of 17 runs, di-

vided into four sequential phases. Participants were

instructed to ski safely within their personal limits.

1. Warm-up (2 runs): Participants skied without

feedback to familiarize themselves with the equip-

ment and environment.

2. Baseline (5 runs): Data were collected using the

embedded sensors, but no feedback was shown.

3. Intervention (M1, 5 runs): The SkiTip Display

system was activated, and color-coded feedback

was presented after each run.

4. Intervention (M2, 5 runs): The SkiTip Display

system was activated, and color-coded feedback

was presented after each run.

The sequence was kept consistent across participants

to minimize confusion and to ensure system stabil-

ity in early use. To support within-subject compari-

son, each participant used the same ski set throughout.

Environmental conditions were recorded per session

(temperature, visibility, slope crowding) to contextu-

alize potential performance variations.

4.3 Data Collection and Measures

Quantitative data were collected using the integrated

IMU and GNSS units. For each run, average carving

angles for left and right turns were computed post-run

using a ﬁxed segmentation threshold based on turn

initiation. The resulting angles were used to derive

a per-run mean angle metric. At the end of the ses-

sion, a short semi-structured interview was conducted

with each participant to gather qualitative feedback

on the system’s usability, understandability, and per-

ceived value.

4.4 Data Analysis

Quantitative results were analyzed descriptively. Due

to the small sample size, no inferential statistics were

performed. Aggregated mean carving angles were

plotted for each participant across the three phases

(Baseline, M1, M2) to visualize trends. Qualitative

responses were coded using thematic analysis with

two rounds of open coding. Key themes related to vis-

ibility and timing, motivation and engagement, cog-

nitive load, and perceived accuracy and trust were ex-

tracted and are reported in Section 6.

5 RESULTS

The results are reported in two parts: (1) quantitative

performance data derived from sensor-based carv-

ing angle estimates, and (2) qualitative ﬁndings from

post-study interviews.

5.1 Carving Angle Metrics

A total of 135 skiing runs were recorded (15 runs per

participant across 9 participants). For each run, left

and right carving angles were computed, and a mean

value was derived. Figure 5 shows the mean carving

angles across three phases: Baseline (no feedback),

M1 (after 5 feedback runs), and M2 (after 10 feedback

runs). While some participants exhibited gradual in-

creases in average carving angle over the interven-

tion period (e.g., P1, P2, P4), others showed inconsis-

tent or plateaued performance. Minor decreases were

observed between M1 and M2 in a subset of partic-

ipants, potentially attributable to fatigue or environ-

mental changes. No statistical signiﬁcance was tested

due to the small sample size and uncontrolled envi-

ronmental conditions. However, individual trajecto-

ries suggest that some participants may have adapted

their turning behavior in response to feedback.

5.2 Qualitative Findings

Thematic analysis of interview transcripts revealed

four primary themes:

Visibility and Timing: Most participants re-

ported that the display was clearly visible when sta-

tionary at the bottom of the run. Several noted that

feedback was best interpreted immediately after stop-

ping: “I liked that it lit up right away when I stopped;

I didn’t have to think back too far” (P4).

Motivation and Engagement: The visual feed-

back was seen as motivational by some participants.

P2 stated, “It made me want to see more green — it

gave me something to aim for.”

Cognitive Load: No participants reported distrac-

tion during skiing. Several indicated that not having

feedback mid-run was beneﬁcial: “I could ski nor-

mally, and then reﬂect after. That’s better than trying

to think during turns” (P7).

Perceived Accuracy and Trust: Opinions var-

ied on whether the display reﬂected true performance.

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Figure 5: Mean carving angles per participant over three phases: Baseline (no feedback), M1 (after 5 feedback runs), and M2

(after 10 feedback runs).

While P5 remarked, “it matched how the run felt,”

others were less certain, noting lack of clarity on how

the values were calculated.

6 DISCUSSION

This section reﬂects on key insights gained from eval-

uating ski-mounted visual feedback in realistic condi-

tions. We summarize practical lessons learned, dis-

cuss methodological challenges in ﬁeld deployments,

acknowledge study limitations, and propose direc-

tions for future work.

6.1 Lessons from Embedded Visual

Feedback in Skiing

L1: Equipment-mounted terminal visual feedback

supports reﬂection but not real-time correction.

Participants consistently reported that the visual feed-

back was helpful for post-run interpretation but not

actionable mid-run, due to both motion dynamics and

visibility constraints. This supports prior observa-

tions that in high-speed sports, embedded displays

may serve better as terminal feedback channels rather

than concurrent guides (Sigrist et al., 2013).

L2: Simplicity in feedback encoding fosters us-

ability. Color-coded outputs were generally found

intuitive, even without prior calibration or explana-

tion. Participants valued the immediate interpretabil-

ity (“More green light on the ski felt like a reward” –

P4). This reinforces earlier ﬁndings from shoe-based

systems (Colley et al., 2018) that low-complexity vi-

sual signals are sufﬁcient for skill reﬂection in sports

contexts.

L3: Motivation was enhanced by goal-oriented

visual feedback. While not all participants improved

their carving angle, several explicitly described the

feedback as motivating. The act of comparing their

own runs (“was that more green than last time?” – P2)

appears to support self-regulated engagement. How-

ever, this effect may be sensitive to fatigue, novelty

loss, or slope variability. All participants felt moti-

vated by the immediate visual comparison of the cur-

rent run (green area) and the previous run (purple bar).

L4: Trust and transparency must be supported

through metric design. A number of participants

questioned the source and meaning of the feedback.

Without an explanation of how carving angles were

derived, conﬁdence in the system varied. Transparent

feedback logic and optional metric breakdowns could

enhance trust and user agency in future designs.

6.2 Methodological Considerations for

In-the-Wild Ski Studies

MC1: Run segmentation accuracy was heavily de-

pendent on reliable GNSS altitude data, as feedback

was triggered post-run. Missing or erroneous height

readings—particularly due to poor satellite reception

or local atmospheric effects—led to false run detec-

tions. These issues were exacerbated when the study

location was moved to a lower-elevation area with less

consistent satellite coverage. Atmospheric anomalies

(e.g., Sahara dust events) may have also interfered

with signal integrity. For higher reliability, we rec-

ommend combining GNSS with barometric altimeters

and validating run segmentation logic under varying

conditions on a consistent slope.

MC2: Low-temperature effects on power sys-

tems also emerged as a critical constraint. Pre-tests at

–10°C showed that battery life dropped drastically un-

Ski Tip Display: Design and Implementation of an Unobtrusive Ski Mounted Visual Feedback System for Alpine Skiing

197

less components were thermally insulated or actively

warmed. In the ﬁnal deployment, batteries enclosed

in a compact housing and warmed by internal compo-

nents (e.g., voltage regulators) maintained function-

ality. Power-critical components should be housed

together and pre-warmed when operating in sub-zero

environments.

MC3: Snow and weather variability signiﬁ-

cantly inﬂuenced both carving performance and dis-

play visibility. In warmer midday conditions, wet

snow accumulated on skis and obscured the display.

Softer snow also reduced carving force and poten-

tially increased fatigue. Conversely, colder or icy

conditions reduced grip and degraded ski edge per-

formance over time. These environmental factors

should be systematically recorded and, where possi-

ble, studies should be scheduled on groomed, low-

trafﬁc slopes early in the day to reduce variability.

Smaller resorts may offer more stable testing condi-

tions.

6.3 Limitations

Several limitations constrain the generalizability of

our ﬁndings:

• Sample size and control: The ﬁeld study in-

volved nine participants without a control group.

Although small-scale deployments are common

in wearable systems research (e.g., (Van Rhe-

den et al., 2024; Niforatos et al., 2018)), espe-

cially when working with custom hardware or in

ﬁeld environments, such designs typically con-

strain conclusions to preliminary or feasibility-

level claims. The absence of counterbalancing

may also have introduced learning effects.

• Environmental variability: External factors

such as snow quality, lighting, and crowd density

were not controlled. Performance changes may

reﬂect these contextual variations rather than sys-

tem effects.

• Metric scope: The system focused exclusively

on average carving angle. While this is a rele-

vant technique measure, it does not capture other

performance aspects such as turn symmetry, speed

control, or fatigue—factors which could inﬂuence

user interpretation and feedback effectiveness.

6.4 Future Work: Designing for

Embedded Feedback in Winter

Sports

This study illustrates that embedding feedback into

the sports equipment itself—rather than on-body

devices—can support reﬂection while respecting

the physical and attentional constraints of dynamic

sports. The tip of the ski provided a compromise

between peripheral visibility and unobtrusiveness, al-

lowing feedback to remain in the skier’s visual ﬁeld

post-run without interfering during motion. To ad-

dress the limitations of this work, future studies

should endeavor to recruit larger and more represen-

tative samples, implement randomized or counterbal-

anced designs, and test across varied, controlled con-

ditions to substantiate the observed trends.

Future systems might explore:

• Multi-modal feedback to support more diverse

learning strategies.

• Dynamic thresholds or personalized feedback

ranges to increase relevance.

• Integration with instructor tools or comparative

metrics across runs.

ACKNOWLEDGEMENTS

The author would like to thank ATOMIC for pro-

viding skis and the ATOMIC movesense IMUs, as

well as supporting with the preparation of the skiing

equipment. This work was supported by the Austrian

Federal Ministry for Climate Action, Environment,

Energy, Mobility, Innovation and Technology under

Contract No. 2021-0.641.557 and the federal state

of Salzburg under the research program COMET-

Competence Centers for Excellent Technologies-in

the project Digital Motion in Sports, Fitness and Well-

being (DiMo; Contract No. 872574).

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