Stephan Sigg

Aalto University · Department of Communications and Networking

We investigate the use of WiFi Received Signal Strength Information (RSSI) at a mobile phone for the recognition of situations, activities and gestures. In particular, we propose a device-free and passive activity recognition system that does not require any device carried by the user and uses ambient signals. We discuss challenges and lessons lear...

We propose to establish a secure communication channel among devices based on similar audio patterns. Features from ambient audio are used to generate a shared cryptographic key between devices without exchanging information about the ambient audio itself or the features utilized for the key generation process. We explore a common audio-fingerprint...

The authors investigate the classification of FM radio signal fluctuation for monitoring the attention of individuals moving toward a static object. In particular, they distinguish between an empty and populated corridor and, for the latter, determine whether the individuals are moving or standing still and whether they're directing their attention...

We consider the detection of activities from non-cooperating individuals with features obtained on the Radio Frequency channel. Since environmental changes impact the transmission channel between devices, the detection of this alteration can be used to classify environmental situations. We identify relevant features to detect activities of non-acti...

We derive an asymptotically sharp bound on the synchronization speed of a randomized black box optimization technique for closed-loop feedback-based distributed adaptive beamforming in wireless sensor networks. We also show that the feedback function that guides this synchronization process is strong multimodal. Given this knowledge that no local o...

p>In this paper, we propose a novel and efficient privacy-preserving split federated learning (PPSFL) framework, that achieves both privacy protection and model accuracy with reasonable computational and communication cost. We describe the implementations of PPSFL on Multi-layer Perceptron (MLP) and Convolutional Neural Network (CNN) models with di...

p>In this paper, we propose a novel and efficient privacy-preserving split federated learning (PPSFL) framework, that achieves both privacy protection and model accuracy with reasonable computational and communication cost. We describe the implementations of PPSFL on Multi-layer Perceptron (MLP) and Convolutional Neural Network (CNN) models with di...

Recognizing human activities from sensor data is a vital task in various domains, but obtaining diverse and labeled sensor data remains challenging and costly. In this paper, we propose an unsupervised statistical feature-guided diffusion model for sensor-based human activity recognition. The proposed method aims to generate synthetic time-series s...

Radar operation partly overlaps and thus interferes with 5G spectrum bands. Examples are vehicular radar, long-range air traffic control, terminal air traffic control, marine radar, airport surveillance, or also operations in the mmWave band. We propose a mechanism to efficiently share the spectrum resources for communication and radar operation us...

With the growing ubiquitousness of pervasive sensing and toward ambient intelligence, pervasive surveillance becomes a very real privacy threat, where private gesture interaction is likely to be observed and automatically interpreted by other (even benign) pervasive intelligence tools. We propose motion transfer, the example-guided modification of...

Today’s deep neural networks (DNNs) are very accurate when trained on a large amount of data. However, suitable input might not be available or may require extensive data collection. Data sharing is one option to address these issues, but it is generally impractical because of privacy concerns or due to the problematic process of finding a sharing...

Since electromagnetic signals are omnipresent, Radio Frequency (RF)-sensing has the potential to become a universal sensing mechanism with applications in localization, smart-home, retail, gesture recognition, intrusion detection, etc. Two emerging technologies in RF-sensing, namely sensing through Large Intelligent Surfaces (LISs) and mmWave Frequ...

With the advance of machine learning and the Internet of Things (IoT), security and privacy have become critical concerns in mobile services and networks. Transferring data to a central unit violates the privacy of sensitive data. Federated learning mitigates this need to transfer local data by sharing model updates only. However, privacy leakage r...

We present Tesla-Rapture, a gesture recognition system for sparse point clouds generated by mmWave Radars. State of the art gesture recognition models are either too resource consuming or not sufficiently accurate for the integration into real-life scenarios using wearable or constrained equipment such as IoT devices (e.g. Raspberry PI), XR hardwar...

Usably secure ad-hoc device pairing fosters connectivity with hardware which is difficult to access (e.g., implanted) and grants convenience for ad-hoc short-term on-off pairing patterns (e.g. shared public domain). Examples are medical devices or fitness equipment. We present CardioID, an approach to extract features from heart rate variability fo...

Mobile device authentication has been a highly active research topic for over 10 years, with a vast range of methods proposed and analyzed. In related areas, such as secure channel protocols, remote authentication, or desktop user authentication, strong, systematic, and increasingly formal threat models have been established and are used to qualita...

The usage of Reconfigurable Intelligent Surfaces (RIS) in conjunction with Unmanned Ariel Vehicles (UAVs) is being investigated as a way to provide energy-efficient communication to ground users in dense urban areas. In this paper, we devise an optimization scenario to reduce overall energy consumption in the network while guaranteeing certain Qual...

RF-sensing, the analysis and interpretation of movement or environment-induced patterns in received electromagnetic signals, has been actively investigated for more than a decade. Since electromagnetic signals, through cellular communication systems, are omnipresent, RF sensing has the potential to become a universal sensing mechanism with applicat...

We present Tesla-Rapture, a gesture recognition interface for point clouds generated by mmWave Radars. State of the art gesture recognition models are either too resource consuming or not sufficiently accurate for integration into real-life scenarios using wearable or constrained equipment such as IoT devices (e.g. Raspberry PI), XR hardware (e.g....

Ambient intelligence demands collaboration schemes for distributed constrained devices which are not only highly energy efficient in distributed sensing, processing and communication, but which also respect data privacy. Traditional algorithms for distributed processing suffer in Ambient intelligence domains either from limited data privacy, or fro...

With the advance of machine learning and the internet of things (IoT), security and privacy have become key concerns in mobile services and networks. Transferring data to a central unit violates privacy as well as protection of sensitive data while increasing bandwidth demands.Federated learning mitigates this need to transfer local data by sharing...

Worker monitoring and protection in collaborative robot (cobots) industrial environments requires advanced sensing capabilities and flexible solutions to monitor the movements of the operator in close proximity of moving robots. Collaborative robotics is an active research area where Internet of Things (IoT) and novel sensing technologies are expec...

We propose a platform for the integration of passive radio sensing and vision technologies into a cloud-IoT framework that performs real-time channel quality information (CQI) time series processing and analytics. Radio sensing and vision technologies allow to passively detect and track objects or persons by using radio waves as probe signals that...

We introduce Pantomime, a novel mid-air gesture recognition system exploiting spatio-temporal properties of millimeter-wave radio frequency (RF) signals. Pantomime is positioned in a unique region of the RF landscape: mid-resolution mid-range high-frequency sensing, which makes it ideal for motion gesture interaction. We configure a commercial freq...

Mobile device authentication has been a highly active research topic for over 10 years, with a vast range of methods having been proposed and analyzed. In related areas such as secure channel protocols, remote authentication, or desktop user authentication, strong, systematic, and increasingly formal threat models have already been established and...

Voice user interfaces can offer intuitive interaction with our devices, but the usability and audio quality could be further improved if multiple devices could collaborate to provide a distributed voice user interface. To ensure that users’ voices are not shared with unauthorized devices, it is however necessary to design an access management syste...

Worker monitoring and protection in collaborative robot (cobots) industrial environments requires advanced sensing capabilities and flexible solutions to monitor the movements of the operator in close proximity of moving robots. Collaborative robotics is an active research area where Internet of Things (IoT) and novel sensing technologies are expec...

Ballistocardiography is a method to gain detailed information about body movements imparted by the ballistic forces associated with cardiac contraction. We measured using different setups and sensor positions to gain information of a reference signal of healthy adults. We used two resting state recordings and two recordings under physical stress (e...

Ballistocardiography (BCG) has gained more attention due to the fundamental goal of medical intervention in diagnostics and follow-up. BCG is particularly suitable for the study of heart failure, which a recent study has shown. The results of this working group shall be validated and reproduced with another study trial. Therefore, acceleration sens...

In advanced driver assistance systems to conditional automation systems, monitoring of driver state is vital for predicting the driver’s capacity to supervise or maneuver the vehicle in cases of unexpected road events and to facilitate better in-car services. The paper presents a technique that exploits millimeter-wave Doppler radar for 3D head tra...

The rapid growth of user expectations and network technologies has proliferated the service needs of 360-degree video streaming. In the light of the unprecedented bitrates required to deliver entire 360-degree videos, tile-based streaming, which associates viewport and non-viewport tiles with different qualities, has emerged as a promising way to f...

Body movement is one of the most important indicators of sleep quality for elderly people living alone. Body movement is crucial for sleep staging and can be combined with other indicators such as breathing and heart rate to monitor sleep quality. Nevertheless, traditional sleep monitoring methods are inconvenient and may invade users’ privacy. To...

Contemporary personal mobile devices support a variety of authen-tication approaches, featuring different levels of security and usabil-ity. With cameras embedded in smart glasses, seamless, hands-free mobile authentication based on gaze is possible. Gaze authenti-cation relies on knowledge as a secret, and gaze passwords are composed from a series...

Smart glasses allow for gaze gesture passwords as a hands-free form of mobile authentication. However, pupil movements for password input are easily observed by attackers, who thereby can derive the password. In this paper we investigate closed-eye gaze gesture passwords with EOG sensors in smart glasses. We propose an approach to detect and recogn...

We present an approach to isolate the angular response of a human on a receiver-side beamformer when the line of sight is several magnitudes stronger than the human response. The solution is implemented in a 5G testbed using a software-defined radio (SDR) platform. Beamforming with SDRs faces the challenge to train the beamformer to different azimu...

Device-free passive sensing of the human targets using wireless signals have acquired much attention in the recent past because of its importance in many applications including security, heating, ventilation and air conditioning, activity recognition, and elderly care. In this paper, we use receiver-side beamforming to isolate the array response of...

Voice user interfaces have increased in popularity, as they enable natural interaction with different applications using one's voice. To improve their usability and audio quality, several devices could interact to provide a unified voice user interface. However, with devices cooperating and sharing voice-related information, user privacy may be at...

With the growing range of radio technologies and sensors used in next-generation industrial plants, radio-frequency sensing systems hold the potential to generate high-value information. We discuss emerging tools, key technology enablers, and distinct deployment experiences with a focus on communications beyond 5G and future industrial applications...

Gaze gestures bear potential for user input with mobile devices, especially smart glasses, due to being always available and hands-free. So far, gaze gesture recognition approaches have utilized open-eye movements only and disregarded closed-eye movements. This paper is a first investigation of the feasibility of detecting and recognizing closed-ey...

Sports and workout activities have become important parts of modern life. Nowadays, many people track characteristics about their sport activities with their mobile devices, which feature inertial measurement unit (IMU) sensors. In this paper we present a methodology to detect and recognize workout, as well as to count repetitions done in a recogni...

Popularity of mobile apps is traditionally measured by metrics such as the number of downloads, installations, or user ratings. A problem with these measures is that they reflect usage only indirectly. Indeed, retention rates, i.e., the number of days users continue to interact with an installed app, have been suggested to predict successful app li...

Biometric authentication, namely using biometric features for authentication is gaining popularity in recent years as further modalities, such as fingerprint, iris, face, voice, gait, and others are exploited. We explore the effectiveness of three simple Electroencephalography (EEG) related biometric authentication tasks, namely resting, thinking a...

We present a multi-frequency feature set to detect driver’s 3D head and torso movements from fluctuations in the Radio Frequency (RF) channel due to body movements. Current features used for movement detection are based on time-of-flight, received signal strength and channel state information, and come with the limitations of coarse tracking, sensi...

Gait has been proposed as a feature for mobile device pairing across arbitrary positions on the human body. Results indicate that the correlation in gait-based features across different body locations is sufficient to establish secure device pairing. However, the population size of the studies is limited and powerful attackers with e.g. capability...