Wireless personal area networks have emerged as an important communication infrastructure in areas such as at-home healthcare and home automation, independent living and assistive technology, as well as sports and wellness. Wireless personal area networks, including body sensor networks, are becoming more mature and are considered to be a realistic alternative as communication infrastructure for demanding services. However, to transmit data from e.g., an ECG in wireless networks is also a challenge, especially if multiple sensors compete for access. Contention-based networks offer simplicity and utilization advantages, but the drawback is lack of predictable performance. Recipients of data sent in wireless sensor networks need to know whether they can trust the information or not. Performance measurements, monitoring and control is of crucial importance for medical and healthcare applications in wireless sensor networks.

This thesis focuses on development, prototype implementation and evaluation of a performance management system with performance and admission control for wireless sensor networks. Furthermore, an implementation of a new method to compensate for clock drift between multiple wireless sensor nodes is also shown. Errors in time synchronization between nodes in Bluetooth networks, resulting in inadequate data fusion, are also analysed.

Body sensor networking is a rapidly growing technology. Today wearable sensors are used to measure and monitor e.g. pulse, temperature, skin conductance, heart activity, and movement (through GPS or inertial measurement units). Mobile phones can act as coordinating nodes in wireless personal area networks used in home automation, healthcare, sport and wellness e.g. to measure pulse and distance. Integration of data from multiple sources sensors (data fusion) means that data from each sensor node needs to be associated with data from other sensor nodes sampled at approximately the same time. Accurate methods for time synchronization are therefore a necessary prerequisite for reliable data fusion.

This thesis studies time synchronization problems in Bluetooth piconets between multiple wireless sensor nodes connected to a mobile phone that acts as coordinating node. Three different algorithms to enable correct data fusion have been developed, implemented and evaluated. The first is a single clock solution that synchronizes multiple wireless sensor nodes based solely on the mobile phone’s clock. The other two algorithms synchronize the clocks in sensor nodes to the clock in the coordinating node. 

E-Health technology has developed rapidly in the last decade. Body-worn sen- sors have developed from an idea to a reality. Today, wireless sensors can perform functions from measuring heartbeats to advanced motion recognition. However, the integration of the various available solutions is still lacking. The research presented in this thesis examined important issues in wireless sensor networks and mobile phone systems for e-Health applications. The dissertation covers four essential areas for successful integration of IoT communication systems for e-Health. The first area is fusion of sensor data. In the previous licentiate thesis (2013), three algo- rithms were developed to synchronise data from multiple wireless sensors. The dissertation presents a method to merge data from wireless sensors with video streams. That was subsequently applied for automatic fall prevention and fall detec- tion using inertial sensors and a depth camera. The second area is mobile phone centric systems for Wi-Fi device-to-device sensor communication enabling mobility in ambient assisted living (AAL) services. The third area is a real-time monitoring and control system for Bluetooth wireless communication networks. Lastly, the dissertation presents a software framework to iteratively develop, tune and deploy functions in wireless sensor network using dynamic software updating.

Teknikanvändandet inom hälsa har förändrats mycket under det senaste tio åren. Kroppsnära sensorer har gått från att vara en idé till att bli en verklighet. Idag finns trådlösa sensorer som kan mäta allt från hjärtslag till avancerad rörelseigenkänning. Integreringen av de olika tillgängliga lösningarna saknas emellertid fortfarande. Forskningen som presenterades i denna avhandling undersökte viktiga frågor i tråd- lösa sensornät och mobila system för e-hälsovård. Avhandlingen omfattar fyra viktiga områden för framgångsrik integrering av IoT-kommunikationssystem för e- hälsa. Det första området är synkronisering av sensordata. I den tidigare licentiat- uppsatsen (2013) utvecklades tre algoritmer för att synkronisera data från flera trådlösa sensorer. Avhandlingen presenterar även en metod för synkronisering av data från trådlösa sensorer med videoströmmar. Den användes därefter för automa- tisk fallhantering och falldetektering med hjälp av tröghetssensorer och en djupka- mera. Det andra området är analys av sensorkommunikation med Wi-Fi till mobilte- lefon för användarmobilitet. Det tredje området är ett realtidsövervaknings- och kontrollsystem för trådlösa Bluetooth-nätverk. Slutligen presenteras avhandlingen en mjukvara för att iterativt utveckla, ställa in och distribuera funktioner i trådlöst sensornätverk med dynamisk mjukvaruuppdatering.