It’s a fact of nature that a single conversation can be interpreted in very different ways. For people with anxiety or conditions such as Asperger’s, this can make social situations extremely stressful. But what if there was a more objective way to measure and understand our interactions? MIT CSAIL researchers an artificially intelligent, wearable system that can predict if a conversation is happy, sad, or neutral based on a person’s speech patterns and vitals. The device takes an existing research-grade wearable—Samsung’s Simband smartwatch, which can measure movement, heart rate, blood pressure, blood flow, and skin temperature—and pairs it with audio capture that can pick up signals like tone, pitch, energy, and word choice, and provide a transcript of the text. By weighing all of the incoming signals, algorithms can classify each five-second installment of conversation as either “positive” or “negative.”