To foster work in areas: Psychophysiology, Machine learning, Affective computing, Brain-Machine Interfaces and Thermal Imaging,

we open our collected datasets to research communities.

Please contact us ( youngjun[dot]cho[dot]15[at]ucl[dot]ac[dot]uk ) to get permission and password of each dataset.


Robust Tracking of Respiratory Rate (Collection Period: July 2016 – April 2017)

Datasets: [Dataset 1], [Dataset 2], [Dataset 3]


1. Dataset 1: controlled respiration in environments with non-constant temperature

The aim of the first experiment was to carry out a systematic evaluation of our approach in environments with different temperature values and dynamics. 5 healthy adults (2 female) (aged 29-38 years, M=31.4, SD=3.78) were recruited from the university subject pool. Following the protocol used in Gastel et al. (2016), participants were asked to maintain a stable posture and breath according to a set of breathing patterns presented to them on a screen. Figure 5 in Cho et al. (2017) shows the design for this experiment. All the participants were given a thermal camera attached to an Android smartphone to record their face and an additional smartphone that provided the breathing patterns. The three guiding breathing patterns composed of slow (10 breaths/min), normal (15 bpm) and fast speed (30 bpm). Each breathing pattern lasted 30 seconds. The guiding breathing patterns were displayed dynamically on the screen. Participants were given a 60 seconds-training period. Taking advantage of mobile thermal imaging, participants were able to monitor themselves by aiming the camera at their face. The distance between the face and device ranged from 35cm to 55cm. The recordings were repeated in four different places: a controlled room (“Place A”), entrance of the building (wind from outside and heat from inside) (“Place B”), a street corner (windy) (“Place C”) and park (“Place D”) in winter. The collected dataset consists of approximately 80 minutes – recordings (5 participants x 4 places x 4 minutes). The person was asked to remain as still as possible.


2.Dataset 2: unconstrained respiration during desk activity with natural motion artifacts

The aim of the second experiment was to test our approach in more realistic unconstrained sedentary desk activities. 10 healthy adults (6 female) (aged 24-31 years, M=28.4, SD=2.17) from a variety of ethnical backgrounds (skin colour: from pale white to black) were recruited from the university subject pool. The pool includes people from outside the university. The experiment was conducted in a quiet laboratory room in summer and simulated desk activity behaviour, consisting of three phases lasting 2 minutes each: i) sitting and conversation, ii) reading a news article on the screen and iii) surfing the internet with the keyboard and mouse. As described in Figure 6 in Cho et al. (2017), the mobile thermal camera was installed near each participant’s face using a shoulder rig and the distance from the face ranged from 35cm to 50cm to account for the spatial resolution (160×120) of the camera. To ensure natural motion artefacts, people were told to act naturally, i.e. no movement constraints were imposed. The collected dataset includes a variety of movement situations, such as head rotations due to people walking behind them with temporary disappearance of the nostril from the thermal camera view. The change in a participant’s position from phase i) to ii) ensured changes in global temperature variance around the nostril-ROI. The experiment resulted in 60 minutes (10 participants x 6 minutes) of thermal video recording of spontaneous breathing patterns, natural movements in sedentary contexts and changes in ambient temperature.


3. Dataset 3: unconstrained respiration in fully mobile context and varying thermal dynamic range scenes

The last experiment aimed to measure the respiration patterns for people undertaking natural, unrestricted actions. In order to enable mobility, the thermal camera was attached to a headset-microphone-shaped rig whose distance from the face ranged between 20cm and 30cm as shown in Figure 6 in Cho et al. (2017). We recruited 8 healthy adults (5 female), aged 23-31 years (M=27.0, SD=2.93) from various ethnical backgrounds. To simulate a variety of fully unconstrained situations, the experiment had two main sessions: i) indoor physical activity and ii) outdoor physical activity. The first session consisted of three tasks of 2 minutes each: walking through a corridor, standing in a dark room while doing small movement and climbing and descending stairs. The second session was carried out outdoor on a street pavement and in a windy park to involve varying thermal dynamic range scenes. During the session, subjects were guided to walk slow, walk fast, and stroll in natural paces. Each walking pattern lasted 2 minutes. All sessions were run in the summer. The final dataset includes thermal imaging sequences of approximately 96 minutes (8 participants x 2 sessions x 3 activities x 2 minutes).



Youngjun Cho, Simon J. Julier, Nicolai Marquardt, and Nadia Bianchi-Berthouze, “Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging,” Biomed. Opt. Express 8, 4480-4503 (2017)

DOI: 10.1364/BOE.8.004480.



DeepBreath (Collection Period: March 2017 – May 2017)

Datasets: [Dataset]

Description: (To be available soon in ACII 2017)